Release to main (#239)

* [With Mintox] Copy M4Tv2 and Expressive gradio space demo to SC (#233)

* M4T & expressivity gradio

* revert undesired changes

* mintox update

* M4T & expressivity gradio

* revert undesired changes

* mintox update

* Fix large model loading in unity.cpp

* final license (#231)

* Update README.md

* Create seamless_align_expressive_README

* Update seamless_align_README.md

* Update SEAMLESS_LICENSE

CC_BY_NC_LICENSE

@@ -1,400 +0,0 @@
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-Creative Commons Attribution-NonCommercial 4.0 International Public
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-By exercising the Licensed Rights (defined below), You accept and agree
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-          the Licensor or others designated to receive attribution as
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-       1. Moral rights, such as the right of integrity, are not
-          licensed under this Public License, nor are publicity,
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CONTRIBUTING.md

@@ -34,4 +34,4 @@ outlined on that page and do not file a public issue.
 
 ## License
 By contributing to `seamless_communication`, you agree that your contributions will be licensed
-under the LICENSE file in the root directory of this source tree.
+under the MIT_LICENSE file in the root directory of this source tree.

LICENSE

@@ -1,21 +1,400 @@
-MIT License
-
-Copyright (c) Meta Platforms, Inc. and affiliates.
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
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-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+
+Attribution-NonCommercial 4.0 International
+
+=======================================================================
+
+Creative Commons Corporation ("Creative Commons") is not a law firm and
+does not provide legal services or legal advice. Distribution of
+Creative Commons public licenses does not create a lawyer-client or
+other relationship. Creative Commons makes its licenses and related
+information available on an "as-is" basis. Creative Commons gives no
+warranties regarding its licenses, any material licensed under their
+terms and conditions, or any related information. Creative Commons
+disclaims all liability for damages resulting from their use to the
+fullest extent possible.
+
+Using Creative Commons Public Licenses
+
+Creative Commons public licenses provide a standard set of terms and
+conditions that creators and other rights holders may use to share
+original works of authorship and other material subject to copyright
+and certain other rights specified in the public license below. The
+following considerations are for informational purposes only, are not
+exhaustive, and do not form part of our licenses.
+
+     Considerations for licensors: Our public licenses are
+     intended for use by those authorized to give the public
+     permission to use material in ways otherwise restricted by
+     copyright and certain other rights. Our licenses are
+     irrevocable. Licensors should read and understand the terms
+     and conditions of the license they choose before applying it.
+     Licensors should also secure all rights necessary before
+     applying our licenses so that the public can reuse the
+     material as expected. Licensors should clearly mark any
+     material not subject to the license. This includes other CC-
+     licensed material, or material used under an exception or
+     limitation to copyright. More considerations for licensors:
+	wiki.creativecommons.org/Considerations_for_licensors
+
+     Considerations for the public: By using one of our public
+     licenses, a licensor grants the public permission to use the
+     licensed material under specified terms and conditions. If
+     the licensor's permission is not necessary for any reason--for
+     example, because of any applicable exception or limitation to
+     copyright--then that use is not regulated by the license. Our
+     licenses grant only permissions under copyright and certain
+     other rights that a licensor has authority to grant. Use of
+     the licensed material may still be restricted for other
+     reasons, including because others have copyright or other
+     rights in the material. A licensor may make special requests,
+     such as asking that all changes be marked or described.
+     Although not required by our licenses, you are encouraged to
+     respect those requests where reasonable. More_considerations
+     for the public:
+	wiki.creativecommons.org/Considerations_for_licensees
+
+=======================================================================
+
+Creative Commons Attribution-NonCommercial 4.0 International Public
+License
+
+By exercising the Licensed Rights (defined below), You accept and agree
+to be bound by the terms and conditions of this Creative Commons
+Attribution-NonCommercial 4.0 International Public License ("Public
+License"). To the extent this Public License may be interpreted as a
+contract, You are granted the Licensed Rights in consideration of Your
+acceptance of these terms and conditions, and the Licensor grants You
+such rights in consideration of benefits the Licensor receives from
+making the Licensed Material available under these terms and
+conditions.
+
+Section 1 -- Definitions.
+
+  a. Adapted Material means material subject to Copyright and Similar
+     Rights that is derived from or based upon the Licensed Material
+     and in which the Licensed Material is translated, altered,
+     arranged, transformed, or otherwise modified in a manner requiring
+     permission under the Copyright and Similar Rights held by the
+     Licensor. For purposes of this Public License, where the Licensed
+     Material is a musical work, performance, or sound recording,
+     Adapted Material is always produced where the Licensed Material is
+     synched in timed relation with a moving image.
+
+  b. Adapter's License means the license You apply to Your Copyright
+     and Similar Rights in Your contributions to Adapted Material in
+     accordance with the terms and conditions of this Public License.
+
+  c. Copyright and Similar Rights means copyright and/or similar rights
+     closely related to copyright including, without limitation,
+     performance, broadcast, sound recording, and Sui Generis Database
+     Rights, without regard to how the rights are labeled or
+     categorized. For purposes of this Public License, the rights
+     specified in Section 2(b)(1)-(2) are not Copyright and Similar
+     Rights.
+  d. Effective Technological Measures means those measures that, in the
+     absence of proper authority, may not be circumvented under laws
+     fulfilling obligations under Article 11 of the WIPO Copyright
+     Treaty adopted on December 20, 1996, and/or similar international
+     agreements.
+
+  e. Exceptions and Limitations means fair use, fair dealing, and/or
+     any other exception or limitation to Copyright and Similar Rights
+     that applies to Your use of the Licensed Material.
+
+  f. Licensed Material means the artistic or literary work, database,
+     or other material to which the Licensor applied this Public
+     License.
+
+  g. Licensed Rights means the rights granted to You subject to the
+     terms and conditions of this Public License, which are limited to
+     all Copyright and Similar Rights that apply to Your use of the
+     Licensed Material and that the Licensor has authority to license.
+
+  h. Licensor means the individual(s) or entity(ies) granting rights
+     under this Public License.
+
+  i. NonCommercial means not primarily intended for or directed towards
+     commercial advantage or monetary compensation. For purposes of
+     this Public License, the exchange of the Licensed Material for
+     other material subject to Copyright and Similar Rights by digital
+     file-sharing or similar means is NonCommercial provided there is
+     no payment of monetary compensation in connection with the
+     exchange.
+
+  j. Share means to provide material to the public by any means or
+     process that requires permission under the Licensed Rights, such
+     as reproduction, public display, public performance, distribution,
+     dissemination, communication, or importation, and to make material
+     available to the public including in ways that members of the
+     public may access the material from a place and at a time
+     individually chosen by them.
+
+  k. Sui Generis Database Rights means rights other than copyright
+     resulting from Directive 96/9/EC of the European Parliament and of
+     the Council of 11 March 1996 on the legal protection of databases,
+     as amended and/or succeeded, as well as other essentially
+     equivalent rights anywhere in the world.
+
+  l. You means the individual or entity exercising the Licensed Rights
+     under this Public License. Your has a corresponding meaning.
+
+Section 2 -- Scope.
+
+  a. License grant.
+
+       1. Subject to the terms and conditions of this Public License,
+          the Licensor hereby grants You a worldwide, royalty-free,
+          non-sublicensable, non-exclusive, irrevocable license to
+          exercise the Licensed Rights in the Licensed Material to:
+
+            a. reproduce and Share the Licensed Material, in whole or
+               in part, for NonCommercial purposes only; and
+
+            b. produce, reproduce, and Share Adapted Material for
+               NonCommercial purposes only.
+
+       2. Exceptions and Limitations. For the avoidance of doubt, where
+          Exceptions and Limitations apply to Your use, this Public
+          License does not apply, and You do not need to comply with
+          its terms and conditions.
+
+       3. Term. The term of this Public License is specified in Section
+          6(a).
+
+       4. Media and formats; technical modifications allowed. The
+          Licensor authorizes You to exercise the Licensed Rights in
+          all media and formats whether now known or hereafter created,
+          and to make technical modifications necessary to do so. The
+          Licensor waives and/or agrees not to assert any right or
+          authority to forbid You from making technical modifications
+          necessary to exercise the Licensed Rights, including
+          technical modifications necessary to circumvent Effective
+          Technological Measures. For purposes of this Public License,
+          simply making modifications authorized by this Section 2(a)
+          (4) never produces Adapted Material.
+
+       5. Downstream recipients.
+
+            a. Offer from the Licensor -- Licensed Material. Every
+               recipient of the Licensed Material automatically
+               receives an offer from the Licensor to exercise the
+               Licensed Rights under the terms and conditions of this
+               Public License.
+
+            b. No downstream restrictions. You may not offer or impose
+               any additional or different terms or conditions on, or
+               apply any Effective Technological Measures to, the
+               Licensed Material if doing so restricts exercise of the
+               Licensed Rights by any recipient of the Licensed
+               Material.
+
+       6. No endorsement. Nothing in this Public License constitutes or
+          may be construed as permission to assert or imply that You
+          are, or that Your use of the Licensed Material is, connected
+          with, or sponsored, endorsed, or granted official status by,
+          the Licensor or others designated to receive attribution as
+          provided in Section 3(a)(1)(A)(i).
+
+  b. Other rights.
+
+       1. Moral rights, such as the right of integrity, are not
+          licensed under this Public License, nor are publicity,
+          privacy, and/or other similar personality rights; however, to
+          the extent possible, the Licensor waives and/or agrees not to
+          assert any such rights held by the Licensor to the limited
+          extent necessary to allow You to exercise the Licensed
+          Rights, but not otherwise.
+
+       2. Patent and trademark rights are not licensed under this
+          Public License.
+
+       3. To the extent possible, the Licensor waives any right to
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+     minimum extent necessary to make it enforceable. If the provision
+     cannot be reformed, it shall be severed from this Public License
+     without affecting the enforceability of the remaining terms and
+     conditions.
+
+  c. No term or condition of this Public License will be waived and no
+     failure to comply consented to unless expressly agreed to by the
+     Licensor.
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+=======================================================================
+
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+licenses. Notwithstanding, Creative Commons may elect to apply one of
+its public licenses to material it publishes and in those instances
+will be considered the “Licensor.” The text of the Creative Commons
+public licenses is dedicated to the public domain under the CC0 Public
+Domain Dedication. Except for the limited purpose of indicating that
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+public licenses.
+
+Creative Commons may be contacted at creativecommons.org.

MIT_LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) Meta Platforms, Inc. and affiliates.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -12,13 +12,13 @@ SeamlessM4T models support the tasks of:
 
 :star2: We are releasing SemalessM4T v2, an updated version with our novel *UnitY2* architecture. This new model improves over SeamlessM4T v1 in quality as well as inference latency in speech generation tasks.
 
-To learn more about the collection of SeamlessM4T models, the approach used in each, their language coverage and their performance, visit the [SeamlessM4T README](docs/m4t/README.md)
+To learn more about the collection of SeamlessM4T models, the approach used in each, their language coverage and their performance, visit the [SeamlessM4T README](docs/m4t/README.md) or [🤗 Model Card](https://huggingface.co/facebook/seamless-m4t-v2-large)
 
 ## SeamlessExpressive
 
 SeamlessExpressive is a speech-to-speech translation model that captures certain underexplored aspects of prosody such as speech rate and pauses, while preserving the style of one's voice and high content translation quality.
 
-To learn more about SeamlessExpressive models, visit the [SeamlessExpressive README](docs/expressive/README.md)
+To learn more about SeamlessExpressive models, visit the [SeamlessExpressive README](docs/expressive/README.md) or [🤗 Model Card](https://huggingface.co/facebook/seamless-expressive)
 
 
 ## SeamlessStreaming
@@ -30,21 +30,29 @@ The SeamlessStreaming model supports the following tasks:
 - Speech-to-text translation (S2TT)
 - Automatic speech recognition (ASR)
 
+To learn more about SeamlessStreaming models, visit the [SeamlessStreaming README](docs/streaming/README.md) or [🤗 Model Card](https://huggingface.co/facebook/seamless-streaming)
+
 ## Seamless
 
 The Seamless model is the unified model for expressive streaming speech-to-speech translations.
 
 ## Links
-[Blog]
+### Blog
+[AI at Meta Blog](https://ai.meta.com/research/seamless-communication/)
+### Papers
+[Seamless](https://ai.facebook.com/research/publications/seamless-multilingual-expressive-and-streaming-speech-translation/)
+
+[EMMA](https://ai.meta.com/research/publications/efficient-monotonic-multihead-attention/)
+
+[SONAR](https://ai.meta.com/research/publications/sonar-expressive-zero-shot-expressive-speech-to-speech-translation/)
 
-[Paper]
 
-[Demos]
+### Demos
 
-||SeamlessM4T v2 | SeamlessExpressive | SeamlessStreaming |
-|----|-------- | -------- | -------- |
-|Demo| [SeamlessM4T v2 Demo](https://seamless.metademolab.com/m4t?utm_source=github&utm_medium=web&utm_campaign=seamless&utm_content=readme) | [SeamlessExpressive Demo](https://seamless.metademolab.com/expressive?utm_source=github&utm_medium=web&utm_campaign=seamless&utm_content=readme)  |  |
-|HuggingFace Space Demo|[🤗 SeamlessM4T v2 Space](https://huggingface.co/spaces/facebook/seamless-m4t-v2-large)| [🤗 SeamlessExpressive Space](https://huggingface.co/spaces/facebook/seamless-expressive) |[🤗 SeamlessStreaming Space](https://huggingface.co/spaces/facebook/seamless-streaming)|
+|                        | SeamlessM4T v2                                                                                                                        | SeamlessExpressive                                                                                                                               | SeamlessStreaming                                                                      |
+| ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------- |
+| Demo                   | [SeamlessM4T v2 Demo](https://seamless.metademolab.com/m4t?utm_source=github&utm_medium=web&utm_campaign=seamless&utm_content=readme) | [SeamlessExpressive Demo](https://seamless.metademolab.com/expressive?utm_source=github&utm_medium=web&utm_campaign=seamless&utm_content=readme) |                                                                                          |
+| HuggingFace Space Demo | [🤗 SeamlessM4T v2 Space](https://huggingface.co/spaces/facebook/seamless-m4t-v2-large)                                                | [🤗 SeamlessExpressive Space](https://huggingface.co/spaces/facebook/seamless-expressive)                                                         | [🤗 SeamlessStreaming Space](https://huggingface.co/spaces/facebook/seamless-streaming) |
 
 ## What's new
 
@@ -112,7 +120,7 @@ python src/seamless_communication/cli/expressivity/evaluate/pretssel_inference.p
 You can duplicate the [SeamlessStreaming HF space](https://huggingface.co/spaces/facebook/seamless-streaming?duplicate=true) to run the streaming demo.
 
 
-You can also run the demo locally, by cloning the space from [here](https://huggingface.co/spaces/facebook/seamless-streaming/tree/main). See the README of the SeamlessStreaming HF repo for more details on installation.
+You can also run the demo locally, by cloning the space from [here](https://huggingface.co/spaces/facebook/seamless-streaming/tree/main). See the [README](https://huggingface.co/spaces/facebook/seamless-streaming/blob/main/README.md) of the SeamlessStreaming HF repo for more details on installation.
 
 ## Running SeamlessM4T & SeamlessExpressive [Gradio](https://github.com/gradio-app/gradio) demos locally
 
@@ -127,11 +135,11 @@ python app.py
 # Resources and usage
 ## Model
 ### SeamlessM4T models
-| Model Name         | #params | checkpoint                                                                              | metrics                                                                              |
-| ------------------ | ------- | --------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------ |
-| SeamlessM4T-Large v2  | 2.3B    | [🤗 Model card](https://huggingface.co/facebook/seamless-m4t-v2-large) - [checkpoint](https://dl.fbaipublicfiles.com/seamless/models/seamlessM4T_v2_large.pt)   | [metrics](https://dl.fbaipublicfiles.com/seamless/metrics/seamlessM4T_large_v2.zip)  |
-| SeamlessM4T-Large (v1) | 2.3B    | [🤗 Model card](https://huggingface.co/facebook/seamless-m4t-large) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-large/resolve/main/multitask_unity_large.pt)   | [metrics](https://dl.fbaipublicfiles.com/seamless/metrics/seamlessM4T_large.zip)  |
-| SeamlessM4T-Medium (v1) | 1.2B    | [🤗 Model card](https://huggingface.co/facebook/seamless-m4t-medium) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-medium/resolve/main/multitask_unity_medium.pt) | [metrics](https://dl.fbaipublicfiles.com/seamless/metrics/seamlessM4T_medium.zip) |
+| Model Name              | #params | checkpoint                                                                                                                                                                     | metrics                                                                             |
+| ----------------------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------- |
+| SeamlessM4T-Large v2    | 2.3B    | [🤗 Model card](https://huggingface.co/facebook/seamless-m4t-v2-large) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-v2-large/resolve/main/seamlessM4T_v2_large.pt  )                   | [metrics](https://dl.fbaipublicfiles.com/seamless/metrics/seamlessM4T_large_v2.zip) |
+| SeamlessM4T-Large (v1)  | 2.3B    | [🤗 Model card](https://huggingface.co/facebook/seamless-m4t-large) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-large/resolve/main/multitask_unity_large.pt)    | [metrics](https://dl.fbaipublicfiles.com/seamless/metrics/seamlessM4T_large.zip)    |
+| SeamlessM4T-Medium (v1) | 1.2B    | [🤗 Model card](https://huggingface.co/facebook/seamless-m4t-medium) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-medium/resolve/main/multitask_unity_medium.pt) | [metrics](https://dl.fbaipublicfiles.com/seamless/metrics/seamlessM4T_medium.zip)   |
 
 ### SeamlessExpressive models
 
@@ -139,12 +147,12 @@ python app.py
 
 To access and download SeamlessExpressive, please request the model artifacts through [this request form](https://ai.meta.com/resources/models-and-libraries/seamless-downloads/). Upon approval, you will then receive an email with download links to each model artifact.
 
-Please note that SeamlessExpressive is made available under its own [License]() and [Acceptable Use Policy]().
+Please note that SeamlessExpressive is made available under its own [License](SEAMLESS_LICENSE) and [Acceptable Use Policy](ACCEPTABLE_USE_POLICY).
 
 ### SeamlessStreaming models
-| Model Name         | #params | checkpoint                                                                              | metrics                                                                              |
-| ------------------ | ------- | --------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------ |
-| SeamlessStreaming  | 2.5B    | [🤗 Model card](https://huggingface.co/facebook/seamless-streaming) - [monotonic decoder checkpoint](https://dl.fbaipublicfiles.com/seamless/models/seamless_streaming_monotonic_decoder.pt) - [streaming UnitY2 checkpoint](https://dl.fbaipublicfiles.com/seamless/models/seamless_streaming_unity.pt)  | [metrics](https://dl.fbaipublicfiles.com/seamless/metrics/streaming/seamless_streaming.zip)  |
+| Model Name        | #params | checkpoint                                                                                                                                                                                                                                                                                              | metrics                                                                                     |
+| ----------------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- |
+| SeamlessStreaming | 2.5B    | [🤗 Model card](https://huggingface.co/facebook/seamless-streaming) - [monotonic decoder checkpoint](https://huggingface.co/facebook/seamless-streaming/resolve/main/seamless_streaming_monotonic_decoder.pt) - [streaming UnitY2 checkpoint](https://huggingface.co/facebook/seamless-streaming/resolve/main/seamless_streaming_unity.pt) | [metrics](https://dl.fbaipublicfiles.com/seamless/metrics/streaming/seamless_streaming.zip) |
 
 ### Seamless models
 Seamless model is simply the SeamlessStreaming model with the non-expressive `vocoder_v2` swapped out with the expressive `vocoder_pretssel`.
@@ -176,6 +184,10 @@ For details of build and more usage please checkout [unity.cpp](ggml)
 
 We created two expressive speech-to-speech translation datasets, mExpresso and mDRAL, between English and five other languages -- French, German, Italian, Mandarin and Spanish. We currently open source the speech-to-text of mExpresso for out-of-English directions, and we will open source the remaining part of the datasets soon. For details, please checkout [README](docs/expressive/README.md#benchmark-datasets)
 
+### SeamlessAlignExpressive
+We’re introducing the first expressive speech alignment procedure. Starting with raw data, the expressive alignment procedure automatically discovers pairs of audio segments sharing not only the same meaning, but the same overall expressivity. To showcase this procedure, we are making metadata available to create a benchmarking dataset called SeamlessAlignExpressive, that can be used to validate the quality of our alignment method. SeamlessAlignExpressive is the first large-scale (11k+ hours) collection of multilingual audio alignments for expressive translation. More details can be found on the [SeamlessAlignExpressive README](docs/expressive/seamless_align_expressive_README.md).
+
+
 ## Converting raw audio to units
 Please check out the [README here](src/seamless_communication/cli/m4t/audio_to_units). Note that SeamlessM4T v1 model uses reduced units and other models use non-reduced units.
 
@@ -208,7 +220,6 @@ Apart from Seamless-M4T large (2.3B) and medium (1.2B) models, we are also relea
 We open-source the metadata to SeamlessAlign, the largest open dataset for multimodal translation, totaling 270k+ hours of aligned Speech and Text data. The dataset can be rebuilt by the community based on the [SeamlessAlign readme](docs/m4t/seamless_align_README.md).
 
 
-
 # Citation
 If you use Seamless in your work or any models/datasets/artifacts published in Seamless, please cite :
 
@@ -225,13 +236,13 @@ If you use Seamless in your work or any models/datasets/artifacts published in S
 
 We have three license categories.
 
-The following non-generative components are MIT licensed as found in [LICENSE](LICENSE):
+The following non-generative components are MIT licensed as found in [MIT_LICENSE](MIT_LICENSE):
 - Code
 - Text only part of the mExpresso dataset found in the [SeamlessExpressive README](docs/expressive/README.md).
 - UnitY2 forced alignment extractor found in the [UnitY2 Aligner README](docs/m4t/unity2_aligner_README.md).
 - Speech toxicity tool with the etox dataset found in the [Toxicity README](src/seamless_communication/cli/toxicity).
 
-The following models are CC-BY-NC 4.0 licensed as found in the [CC_BY_NC_LICENSE](CC_BY_NC_LICENSE):
+The following models are CC-BY-NC 4.0 licensed as found in the [LICENSE](LICENSE):
 - SeamlessM4T models (v1 and v2).
 - SeamlessStreaming models.
 

SEAMLESS_LICENSE

@@ -2,7 +2,7 @@ Seamless Licensing Agreement
 
 “Agreement” means this “Seamless Licensing Agreement”, including, the terms and conditions for use, reproduction, distribution and modification of the Seamless Materials set forth herein.
 
-“Documentation” means the specifications, manuals and documentation accompanying Seamless distributed by Meta at [INSERT RESOURCE HYPERLINK].
+“Documentation” means the specifications, manuals and documentation accompanying Seamless distributed by Meta at [https://ai.meta.com/resources/models-and-libraries/seamless-downloads](https://ai.meta.com/resources/models-and-libraries/seamless-downloads).
 
 “Licensee” or “you” means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entity’s behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.
 
@@ -10,7 +10,7 @@ Seamless Licensing Agreement
 
 “Noncommercial Research Uses” means noncommercial research use cases related to research, development, education, processing, or analysis in each case with no direct or indirect commercial gain to you or others.
 
-“Seamless” means the foundational translation and transcription models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code, demonstration materials and other elements of the foregoing distributed by Meta at [INSERT RESOURCE HYPERLINK].
+“Seamless” means the foundational translation and transcription models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code, demonstration materials and other elements of the foregoing distributed by Meta at [https://ai.meta.com/resources/models-and-libraries/seamless-downloads](https://ai.meta.com/resources/models-and-libraries/seamless-downloads).
 
 “Seamless Materials” means, collectively, Meta’s proprietary Seamless and Documentation (and any portion thereof) made available under this Agreement.
 
@@ -25,7 +25,7 @@ By clicking “I Accept” below or by using or distributing any portion or elem
         ii. If you submit for publication the results of research you perform on, using, or otherwise in connection with Seamless Materials, you must acknowledge the use of Seamless Materials in your publication as follows (or an equivalent acknowledgement of your choosing): “This material is based on work supported by the Seamless Licensing Agreement, Copyright © Meta Platforms, Inc. All Rights Reserved.”
         iii. If you receive Seamless Materials, or any derivative works thereof, from a Licensee as part of an integrated end user product, then Section 2 of this Agreement will not apply to you.
         iv. You must retain in all copies of the Seamless Materials that you distribute the following attribution notice within a “Notice” text file distributed as a part of such copies: “Seamless is licensed under the Seamless Licensing Agreement, Copyright © Meta Platforms, Inc. All Rights Reserved.”
-        v. Your use of the Seamless Materials must comply with applicable laws and regulations (including Trade Control Laws)) and adhere to the Acceptable Use Policy for the Seamless Materials ([INSERT SEAMLESS AUP HYPERLINK]), which is hereby incorporated by reference into this Agreement.
+        v. Your use of the Seamless Materials must comply with applicable laws and regulations (including Trade Control Laws)) and adhere to the Acceptable Use Policy for the Seamless Materials [https://ai.meta.com/resources/models-and-libraries/seamless-use-policy](https://ai.meta.com/resources/models-and-libraries/seamless-use-policy), which is hereby incorporated by reference into this Agreement.
 2. Restrictions. You will not, and will not permit, assist or cause any third party to:
         a. use the Seamless Materials or any outputs or results of the Seamless Materials in connection with any commercial uses or for any uses other than Noncommercial Research Uses;
         b. utilize any equipment, device, software, or other means to circumvent or remove any security or protection used by Meta in connection with the Seamless Materials, or to circumvent or remove any usage restrictions, or to enable functionality disabled by Meta; 
@@ -41,4 +41,4 @@ By clicking “I Accept” below or by using or distributing any portion or elem
         c. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Seamless Materials or Seamless outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses and rights  granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the Seamless Materials.
 7. Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Seamless Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Meta may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Seamless Materials. Sections 3, 4, 5, 6(c),  7,  8 and 9 shall survive the termination of this Agreement.
 8. Governing Law and Jurisdiction. This Agreement will be governed and construed under the laws of the State of California without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of California shall have exclusive jurisdiction of any dispute arising out of this Agreement.
-9. Modifications and Amendments. Meta may modify this Agreement from time to time by posting a revised version at [HYPERLINK]; provided that they are similar in spirit to the current version of the Agreement, but may differ in detail to address new problems or concerns. All such changes will be effective immediately. Your continued use of the Seamless Materials after any modification to this Agreement constitutes your agreement to such modification. Except as provided in this Agreement, no modification or addition to any provision of this Agreement will be binding unless it is in writing and signed by an authorized representative of both you and Meta.
+9. Modifications and Amendments. Meta may modify this Agreement from time to time by posting a revised version at [https://ai.meta.com/resources/models-and-libraries/seamless-license/](https://ai.meta.com/resources/models-and-libraries/seamless-license/); provided that they are similar in spirit to the current version of the Agreement, but may differ in detail to address new problems or concerns. All such changes will be effective immediately. Your continued use of the Seamless Materials after any modification to this Agreement constitutes your agreement to such modification. Except as provided in this Agreement, no modification or addition to any provision of this Agreement will be binding unless it is in writing and signed by an authorized representative of both you and Meta.

demo/expressive/app.py

@@ -0,0 +1,290 @@
+#!/usr/bin/env python
+# Copyright (c) Meta Platforms, Inc. and affiliates
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# MIT_LICENSE file in the root directory of this source tree.
+
+import os
+import pathlib
+import tempfile
+
+import gradio as gr
+import torch
+import torchaudio
+from fairseq2.assets import InProcAssetMetadataProvider, asset_store
+from fairseq2.data import Collater, SequenceData, VocabularyInfo
+from fairseq2.data.audio import (
+    AudioDecoder,
+    WaveformToFbankConverter,
+    WaveformToFbankOutput,
+)
+
+from seamless_communication.inference import SequenceGeneratorOptions
+from fairseq2.generation import NGramRepeatBlockProcessor
+from fairseq2.memory import MemoryBlock
+from fairseq2.typing import DataType, Device
+from huggingface_hub import snapshot_download
+from seamless_communication.inference import BatchedSpeechOutput, Translator, SequenceGeneratorOptions
+from seamless_communication.models.generator.loader import load_pretssel_vocoder_model
+from seamless_communication.models.unity import (
+    UnitTokenizer,
+    load_gcmvn_stats,
+    load_unity_text_tokenizer,
+    load_unity_unit_tokenizer,
+)
+from torch.nn import Module
+from seamless_communication.cli.expressivity.evaluate.pretssel_inference_helper import PretsselGenerator
+
+from utils import LANGUAGE_CODE_TO_NAME
+
+DESCRIPTION = """\
+# Seamless Expressive
+[SeamlessExpressive](https://github.com/facebookresearch/seamless_communication) is a speech-to-speech translation model that captures certain underexplored aspects of prosody such as speech rate and pauses, while preserving the style of one's voice and high content translation quality.
+"""
+
+CACHE_EXAMPLES = os.getenv("CACHE_EXAMPLES") == "1" and torch.cuda.is_available()
+
+CHECKPOINTS_PATH = pathlib.Path(os.getenv("CHECKPOINTS_PATH", "/home/user/app/models"))
+if not CHECKPOINTS_PATH.exists():
+    snapshot_download(repo_id="facebook/seamless-expressive", repo_type="model", local_dir=CHECKPOINTS_PATH)
+    snapshot_download(repo_id="facebook/seamless-m4t-v2-large", repo_type="model", local_dir=CHECKPOINTS_PATH)
+
+# Ensure that we do not have any other environment resolvers and always return
+# "demo" for demo purposes.
+asset_store.env_resolvers.clear()
+asset_store.env_resolvers.append(lambda: "demo")
+
+# Construct an `InProcAssetMetadataProvider` with environment-specific metadata
+# that just overrides the regular metadata for "demo" environment. Note the "@demo" suffix.
+demo_metadata = [
+    {
+        "name": "seamless_expressivity@demo",
+        "checkpoint": f"file://{CHECKPOINTS_PATH}/m2m_expressive_unity.pt",
+        "char_tokenizer": f"file://{CHECKPOINTS_PATH}/spm_char_lang38_tc.model",
+    },
+    {
+        "name": "vocoder_pretssel@demo",
+        "checkpoint": f"file://{CHECKPOINTS_PATH}/pretssel_melhifigan_wm-final.pt",
+    },
+    {
+        "name": "seamlessM4T_v2_large@demo",
+        "checkpoint": f"file://{CHECKPOINTS_PATH}/seamlessM4T_v2_large.pt",
+        "char_tokenizer": f"file://{CHECKPOINTS_PATH}/spm_char_lang38_tc.model",
+    },
+]
+
+asset_store.metadata_providers.append(InProcAssetMetadataProvider(demo_metadata))
+
+LANGUAGE_NAME_TO_CODE = {v: k for k, v in LANGUAGE_CODE_TO_NAME.items()}
+
+
+if torch.cuda.is_available():
+    device = torch.device("cuda:0")
+    dtype = torch.float16
+else:
+    device = torch.device("cpu")
+    dtype = torch.float32
+
+
+MODEL_NAME = "seamless_expressivity"
+VOCODER_NAME = "vocoder_pretssel"
+
+# used for ASR for toxicity
+m4t_translator = Translator(
+    model_name_or_card="seamlessM4T_v2_large",
+    vocoder_name_or_card=None,
+    device=device,
+    dtype=dtype,
+)
+unit_tokenizer = load_unity_unit_tokenizer(MODEL_NAME)
+
+_gcmvn_mean, _gcmvn_std = load_gcmvn_stats(VOCODER_NAME)
+gcmvn_mean = torch.tensor(_gcmvn_mean, device=device, dtype=dtype)
+gcmvn_std = torch.tensor(_gcmvn_std, device=device, dtype=dtype)
+
+translator = Translator(
+    MODEL_NAME,
+    vocoder_name_or_card=None,
+    device=device,
+    dtype=dtype,
+    apply_mintox=False,
+)
+
+text_generation_opts = SequenceGeneratorOptions(
+    beam_size=5,
+    unk_penalty=torch.inf,
+    soft_max_seq_len=(0, 200),
+    step_processor=NGramRepeatBlockProcessor(
+        ngram_size=10,
+    ),
+)
+m4t_text_generation_opts = SequenceGeneratorOptions(
+    beam_size=5,
+    unk_penalty=torch.inf,
+    soft_max_seq_len=(1, 200),
+    step_processor=NGramRepeatBlockProcessor(
+        ngram_size=10,
+    ),
+)
+
+pretssel_generator = PretsselGenerator(
+    VOCODER_NAME,
+    vocab_info=unit_tokenizer.vocab_info,
+    device=device,
+    dtype=dtype,
+)
+
+decode_audio = AudioDecoder(dtype=torch.float32, device=device)
+
+convert_to_fbank = WaveformToFbankConverter(
+    num_mel_bins=80,
+    waveform_scale=2**15,
+    channel_last=True,
+    standardize=False,
+    device=device,
+    dtype=dtype,
+)
+
+
+def normalize_fbank(data: WaveformToFbankOutput) -> WaveformToFbankOutput:
+    fbank = data["fbank"]
+    std, mean = torch.std_mean(fbank, dim=0)
+    data["fbank"] = fbank.subtract(mean).divide(std)
+    data["gcmvn_fbank"] = fbank.subtract(gcmvn_mean).divide(gcmvn_std)
+    return data
+
+
+collate = Collater(pad_value=0, pad_to_multiple=1)
+
+
+AUDIO_SAMPLE_RATE = 16000
+MAX_INPUT_AUDIO_LENGTH = 10  # in seconds
+
+
+def remove_prosody_tokens_from_text(text):
+    # filter out prosody tokens, there is only emphasis '*', and pause '='
+    text = text.replace("*", "").replace("=", "")
+    text = " ".join(text.split())
+    return text
+
+
+def preprocess_audio(input_audio_path: str) -> None:
+    arr, org_sr = torchaudio.load(input_audio_path)
+    new_arr = torchaudio.functional.resample(arr, orig_freq=org_sr, new_freq=AUDIO_SAMPLE_RATE)
+    max_length = int(MAX_INPUT_AUDIO_LENGTH * AUDIO_SAMPLE_RATE)
+    if new_arr.shape[1] > max_length:
+        new_arr = new_arr[:, :max_length]
+        gr.Warning(f"Input audio is too long. Only the first {MAX_INPUT_AUDIO_LENGTH} seconds is used.")
+    torchaudio.save(input_audio_path, new_arr, sample_rate=AUDIO_SAMPLE_RATE)
+
+
+def run(
+    input_audio_path: str,
+    source_language: str,
+    target_language: str,
+) -> tuple[str, str]:
+    target_language_code = LANGUAGE_NAME_TO_CODE[target_language]
+    source_language_code = LANGUAGE_NAME_TO_CODE[source_language]
+
+    preprocess_audio(input_audio_path)
+
+    with pathlib.Path(input_audio_path).open("rb") as fb:
+        block = MemoryBlock(fb.read())
+        example = decode_audio(block)
+
+    example = convert_to_fbank(example)
+    example = normalize_fbank(example)
+    example = collate(example)
+
+    # get transcription for mintox
+    source_sentences, _ = m4t_translator.predict(
+        input=example["fbank"],
+        task_str="S2TT",  # get source text
+        tgt_lang=source_language_code,
+        text_generation_opts=m4t_text_generation_opts,
+    )
+    source_text = str(source_sentences[0])
+
+    prosody_encoder_input = example["gcmvn_fbank"]
+    text_output, unit_output = translator.predict(
+        example["fbank"],
+        "S2ST",
+        tgt_lang=target_language_code,
+        src_lang=source_language_code,
+        text_generation_opts=text_generation_opts,
+        unit_generation_ngram_filtering=False,
+        duration_factor=1.0,
+        prosody_encoder_input=prosody_encoder_input,
+        src_text=source_text,  # for mintox check
+    )
+    speech_output = pretssel_generator.predict(
+        unit_output.units,
+        tgt_lang=target_language_code,
+        prosody_encoder_input=prosody_encoder_input,
+    )
+
+    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
+        torchaudio.save(
+            f.name,
+            speech_output.audio_wavs[0][0].to(torch.float32).cpu(),
+            sample_rate=speech_output.sample_rate,
+        )
+
+    text_out = remove_prosody_tokens_from_text(str(text_output[0]))
+
+    return f.name, text_out
+
+
+TARGET_LANGUAGE_NAMES = [
+    "English",
+    "French",
+    "German",
+    "Spanish",
+]
+
+with gr.Blocks(css="style.css") as demo:
+    gr.Markdown(DESCRIPTION)
+    gr.DuplicateButton(
+        value="Duplicate Space for private use",
+        elem_id="duplicate-button",
+        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
+    )
+    with gr.Row():
+        with gr.Column():
+            with gr.Group():
+                input_audio = gr.Audio(label="Input speech", type="filepath")
+                source_language = gr.Dropdown(
+                    label="Source language",
+                    choices=TARGET_LANGUAGE_NAMES,
+                    value="English",
+                )
+                target_language = gr.Dropdown(
+                    label="Target language",
+                    choices=TARGET_LANGUAGE_NAMES,
+                    value="French",
+                )
+            btn = gr.Button()
+        with gr.Column():
+            with gr.Group():
+                output_audio = gr.Audio(label="Translated speech")
+                output_text = gr.Textbox(label="Translated text")
+
+    gr.Examples(
+        examples=[],
+        inputs=[input_audio, source_language, target_language],
+        outputs=[output_audio, output_text],
+        fn=run,
+        cache_examples=CACHE_EXAMPLES,
+        api_name=False,
+    )
+
+    btn.click(
+        fn=run,
+        inputs=[input_audio, source_language, target_language],
+        outputs=[output_audio, output_text],
+        api_name="run",
+    )
+
+if __name__ == "__main__":
+    demo.queue(max_size=50).launch()

demo/expressive/requirements.txt

@@ -0,0 +1,5 @@
+gradio~=4.5.0
+omegaconf~=2.3.0
+torch~=2.1.0
+torchaudio~=2.1.0
+fairseq2~=0.2.0

demo/expressive/utils.py

@@ -0,0 +1,104 @@
+LANGUAGE_CODE_TO_NAME = {
+    "afr": "Afrikaans",
+    "amh": "Amharic",
+    "arb": "Modern Standard Arabic",
+    "ary": "Moroccan Arabic",
+    "arz": "Egyptian Arabic",
+    "asm": "Assamese",
+    "ast": "Asturian",
+    "azj": "North Azerbaijani",
+    "bel": "Belarusian",
+    "ben": "Bengali",
+    "bos": "Bosnian",
+    "bul": "Bulgarian",
+    "cat": "Catalan",
+    "ceb": "Cebuano",
+    "ces": "Czech",
+    "ckb": "Central Kurdish",
+    "cmn": "Mandarin Chinese",
+    "cym": "Welsh",
+    "dan": "Danish",
+    "deu": "German",
+    "ell": "Greek",
+    "eng": "English",
+    "est": "Estonian",
+    "eus": "Basque",
+    "fin": "Finnish",
+    "fra": "French",
+    "gaz": "West Central Oromo",
+    "gle": "Irish",
+    "glg": "Galician",
+    "guj": "Gujarati",
+    "heb": "Hebrew",
+    "hin": "Hindi",
+    "hrv": "Croatian",
+    "hun": "Hungarian",
+    "hye": "Armenian",
+    "ibo": "Igbo",
+    "ind": "Indonesian",
+    "isl": "Icelandic",
+    "ita": "Italian",
+    "jav": "Javanese",
+    "jpn": "Japanese",
+    "kam": "Kamba",
+    "kan": "Kannada",
+    "kat": "Georgian",
+    "kaz": "Kazakh",
+    "kea": "Kabuverdianu",
+    "khk": "Halh Mongolian",
+    "khm": "Khmer",
+    "kir": "Kyrgyz",
+    "kor": "Korean",
+    "lao": "Lao",
+    "lit": "Lithuanian",
+    "ltz": "Luxembourgish",
+    "lug": "Ganda",
+    "luo": "Luo",
+    "lvs": "Standard Latvian",
+    "mai": "Maithili",
+    "mal": "Malayalam",
+    "mar": "Marathi",
+    "mkd": "Macedonian",
+    "mlt": "Maltese",
+    "mni": "Meitei",
+    "mya": "Burmese",
+    "nld": "Dutch",
+    "nno": "Norwegian Nynorsk",
+    "nob": "Norwegian Bokm\u00e5l",
+    "npi": "Nepali",
+    "nya": "Nyanja",
+    "oci": "Occitan",
+    "ory": "Odia",
+    "pan": "Punjabi",
+    "pbt": "Southern Pashto",
+    "pes": "Western Persian",
+    "pol": "Polish",
+    "por": "Portuguese",
+    "ron": "Romanian",
+    "rus": "Russian",
+    "slk": "Slovak",
+    "slv": "Slovenian",
+    "sna": "Shona",
+    "snd": "Sindhi",
+    "som": "Somali",
+    "spa": "Spanish",
+    "srp": "Serbian",
+    "swe": "Swedish",
+    "swh": "Swahili",
+    "tam": "Tamil",
+    "tel": "Telugu",
+    "tgk": "Tajik",
+    "tgl": "Tagalog",
+    "tha": "Thai",
+    "tur": "Turkish",
+    "ukr": "Ukrainian",
+    "urd": "Urdu",
+    "uzn": "Northern Uzbek",
+    "vie": "Vietnamese",
+    "xho": "Xhosa",
+    "yor": "Yoruba",
+    "yue": "Cantonese",
+    "zlm": "Colloquial Malay",
+    "zsm": "Standard Malay",
+    "zul": "Zulu",
+}

demo/app.py → demo/m4tv1/app.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from __future__ import annotations
 

demo/m4tv2/app.py

@@ -0,0 +1,368 @@
+#!/usr/bin/env python
+# Copyright (c) Meta Platforms, Inc. and affiliates
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# MIT_LICENSE file in the root directory of this source tree.
+
+from __future__ import annotations
+
+import os
+import pathlib
+
+import gradio as gr
+import numpy as np
+import torch
+import torchaudio
+from fairseq2.assets import InProcAssetMetadataProvider, asset_store
+from huggingface_hub import snapshot_download
+from seamless_communication.inference import Translator
+
+from lang_list import (
+    ASR_TARGET_LANGUAGE_NAMES,
+    LANGUAGE_NAME_TO_CODE,
+    S2ST_TARGET_LANGUAGE_NAMES,
+    S2TT_TARGET_LANGUAGE_NAMES,
+    T2ST_TARGET_LANGUAGE_NAMES,
+    T2TT_TARGET_LANGUAGE_NAMES,
+    TEXT_SOURCE_LANGUAGE_NAMES,
+)
+
+CHECKPOINTS_PATH = pathlib.Path(os.getenv("CHECKPOINTS_PATH", "/home/user/app/models"))
+if not CHECKPOINTS_PATH.exists():
+    snapshot_download(repo_id="meta-private/M4Tv2", repo_type="model", local_dir=CHECKPOINTS_PATH)
+asset_store.env_resolvers.clear()
+asset_store.env_resolvers.append(lambda: "demo")
+demo_metadata = [
+    {
+        "name": "seamlessM4T_v2_large@demo",
+        "checkpoint": f"file://{CHECKPOINTS_PATH}/seamlessM4T_v2_large.pt",
+        "char_tokenizer": f"file://{CHECKPOINTS_PATH}/spm_char_lang38_tc.model",
+    },
+    {
+        "name": "vocoder_v2@demo",
+        "checkpoint": f"file://{CHECKPOINTS_PATH}/vocoder_v2.pt",
+    },
+]
+asset_store.metadata_providers.append(InProcAssetMetadataProvider(demo_metadata))
+
+DESCRIPTION = """\
+# SeamlessM4T
+[SeamlessM4T](https://github.com/facebookresearch/seamless_communication) is designed to provide high-quality
+translation, allowing people from different linguistic communities to communicate effortlessly through speech and text.
+This unified model enables multiple tasks like Speech-to-Speech (S2ST), Speech-to-Text (S2TT), Text-to-Speech (T2ST)
+translation and more, without relying on multiple separate models.
+"""
+
+CACHE_EXAMPLES = os.getenv("CACHE_EXAMPLES") == "1" and torch.cuda.is_available()
+
+AUDIO_SAMPLE_RATE = 16000.0
+MAX_INPUT_AUDIO_LENGTH = 60  # in seconds
+DEFAULT_TARGET_LANGUAGE = "French"
+
+if torch.cuda.is_available():
+    device = torch.device("cuda:0")
+    dtype = torch.float16
+else:
+    device = torch.device("cpu")
+    dtype = torch.float32
+
+translator = Translator(
+    model_name_or_card="seamlessM4T_v2_large",
+    vocoder_name_or_card="vocoder_v2",
+    device=device,
+    dtype=dtype,
+    apply_mintox=True,
+)
+
+
+def preprocess_audio(input_audio: str) -> None:
+    arr, org_sr = torchaudio.load(input_audio)
+    new_arr = torchaudio.functional.resample(arr, orig_freq=org_sr, new_freq=AUDIO_SAMPLE_RATE)
+    max_length = int(MAX_INPUT_AUDIO_LENGTH * AUDIO_SAMPLE_RATE)
+    if new_arr.shape[1] > max_length:
+        new_arr = new_arr[:, :max_length]
+        gr.Warning(f"Input audio is too long. Only the first {MAX_INPUT_AUDIO_LENGTH} seconds is used.")
+    torchaudio.save(input_audio, new_arr, sample_rate=int(AUDIO_SAMPLE_RATE))
+
+
+def run_s2st(
+    input_audio: str, source_language: str, target_language: str
+) -> tuple[tuple[int, np.ndarray] | None, str]:
+    preprocess_audio(input_audio)
+    source_language_code = LANGUAGE_NAME_TO_CODE[source_language]
+    target_language_code = LANGUAGE_NAME_TO_CODE[target_language]
+    out_texts, out_audios = translator.predict(
+        input=input_audio,
+        task_str="S2ST",
+        src_lang=source_language_code,
+        tgt_lang=target_language_code,
+    )
+    out_text = str(out_texts[0])
+    out_wav = out_audios.audio_wavs[0].cpu().detach().numpy()
+    return (int(AUDIO_SAMPLE_RATE), out_wav), out_text
+
+
+def run_s2tt(input_audio: str, source_language: str, target_language: str) -> str:
+    preprocess_audio(input_audio)
+    source_language_code = LANGUAGE_NAME_TO_CODE[source_language]
+    target_language_code = LANGUAGE_NAME_TO_CODE[target_language]
+    out_texts, _ = translator.predict(
+        input=input_audio,
+        task_str="S2TT",
+        src_lang=source_language_code,
+        tgt_lang=target_language_code,
+    )
+    return str(out_texts[0])
+
+
+def run_t2st(input_text: str, source_language: str, target_language: str) -> tuple[tuple[int, np.ndarray] | None, str]:
+    source_language_code = LANGUAGE_NAME_TO_CODE[source_language]
+    target_language_code = LANGUAGE_NAME_TO_CODE[target_language]
+    out_texts, out_audios = translator.predict(
+        input=input_text,
+        task_str="T2ST",
+        src_lang=source_language_code,
+        tgt_lang=target_language_code,
+    )
+    out_text = str(out_texts[0])
+    out_wav = out_audios.audio_wavs[0].cpu().detach().numpy()
+    return (int(AUDIO_SAMPLE_RATE), out_wav), out_text
+
+
+def run_t2tt(input_text: str, source_language: str, target_language: str) -> str:
+    source_language_code = LANGUAGE_NAME_TO_CODE[source_language]
+    target_language_code = LANGUAGE_NAME_TO_CODE[target_language]
+    out_texts, _ = translator.predict(
+        input=input_text,
+        task_str="T2TT",
+        src_lang=source_language_code,
+        tgt_lang=target_language_code,
+    )
+    return str(out_texts[0])
+
+
+def run_asr(input_audio: str, target_language: str) -> str:
+    preprocess_audio(input_audio)
+    target_language_code = LANGUAGE_NAME_TO_CODE[target_language]
+    out_texts, _ = translator.predict(
+        input=input_audio,
+        task_str="ASR",
+        src_lang=target_language_code,
+        tgt_lang=target_language_code,
+    )
+    return str(out_texts[0])
+
+
+with gr.Blocks() as demo_s2st:
+    with gr.Row():
+        with gr.Column():
+            with gr.Group():
+                input_audio = gr.Audio(label="Input speech", type="filepath")
+                source_language = gr.Dropdown(
+                    label="Source language",
+                    choices=ASR_TARGET_LANGUAGE_NAMES,
+                    value="English",
+                )
+                target_language = gr.Dropdown(
+                    label="Target language",
+                    choices=S2ST_TARGET_LANGUAGE_NAMES,
+                    value=DEFAULT_TARGET_LANGUAGE,
+                )
+            btn = gr.Button("Translate")
+        with gr.Column():
+            with gr.Group():
+                output_audio = gr.Audio(
+                    label="Translated speech",
+                    autoplay=False,
+                    streaming=False,
+                    type="numpy",
+                )
+                output_text = gr.Textbox(label="Translated text")
+
+    gr.Examples(
+        examples=[],
+        inputs=[input_audio, source_language, target_language],
+        outputs=[output_audio, output_text],
+        fn=run_s2st,
+        cache_examples=CACHE_EXAMPLES,
+        api_name=False,
+    )
+
+    btn.click(
+        fn=run_s2st,
+        inputs=[input_audio, source_language, target_language],
+        outputs=[output_audio, output_text],
+        api_name="s2st",
+    )
+
+with gr.Blocks() as demo_s2tt:
+    with gr.Row():
+        with gr.Column():
+            with gr.Group():
+                input_audio = gr.Audio(label="Input speech", type="filepath")
+                source_language = gr.Dropdown(
+                    label="Source language",
+                    choices=ASR_TARGET_LANGUAGE_NAMES,
+                    value="English",
+                )
+                target_language = gr.Dropdown(
+                    label="Target language",
+                    choices=S2TT_TARGET_LANGUAGE_NAMES,
+                    value=DEFAULT_TARGET_LANGUAGE,
+                )
+            btn = gr.Button("Translate")
+        with gr.Column():
+            output_text = gr.Textbox(label="Translated text")
+
+    gr.Examples(
+        examples=[],
+        inputs=[input_audio, source_language, target_language],
+        outputs=output_text,
+        fn=run_s2tt,
+        cache_examples=CACHE_EXAMPLES,
+        api_name=False,
+    )
+
+    btn.click(
+        fn=run_s2tt,
+        inputs=[input_audio, source_language, target_language],
+        outputs=output_text,
+        api_name="s2tt",
+    )
+
+with gr.Blocks() as demo_t2st:
+    with gr.Row():
+        with gr.Column():
+            with gr.Group():
+                input_text = gr.Textbox(label="Input text")
+                with gr.Row():
+                    source_language = gr.Dropdown(
+                        label="Source language",
+                        choices=TEXT_SOURCE_LANGUAGE_NAMES,
+                        value="English",
+                    )
+                    target_language = gr.Dropdown(
+                        label="Target language",
+                        choices=T2ST_TARGET_LANGUAGE_NAMES,
+                        value=DEFAULT_TARGET_LANGUAGE,
+                    )
+            btn = gr.Button("Translate")
+        with gr.Column():
+            with gr.Group():
+                output_audio = gr.Audio(
+                    label="Translated speech",
+                    autoplay=False,
+                    streaming=False,
+                    type="numpy",
+                )
+                output_text = gr.Textbox(label="Translated text")
+
+    gr.Examples(
+        examples=[],
+        inputs=[input_text, source_language, target_language],
+        outputs=[output_audio, output_text],
+        fn=run_t2st,
+        cache_examples=CACHE_EXAMPLES,
+        api_name=False,
+    )
+
+    gr.on(
+        triggers=[input_text.submit, btn.click],
+        fn=run_t2st,
+        inputs=[input_text, source_language, target_language],
+        outputs=[output_audio, output_text],
+        api_name="t2st",
+    )
+
+with gr.Blocks() as demo_t2tt:
+    with gr.Row():
+        with gr.Column():
+            with gr.Group():
+                input_text = gr.Textbox(label="Input text")
+                with gr.Row():
+                    source_language = gr.Dropdown(
+                        label="Source language",
+                        choices=TEXT_SOURCE_LANGUAGE_NAMES,
+                        value="English",
+                    )
+                    target_language = gr.Dropdown(
+                        label="Target language",
+                        choices=T2TT_TARGET_LANGUAGE_NAMES,
+                        value=DEFAULT_TARGET_LANGUAGE,
+                    )
+            btn = gr.Button("Translate")
+        with gr.Column():
+            output_text = gr.Textbox(label="Translated text")
+
+    gr.Examples(
+        examples=[],
+        inputs=[input_text, source_language, target_language],
+        outputs=output_text,
+        fn=run_t2tt,
+        cache_examples=CACHE_EXAMPLES,
+        api_name=False,
+    )
+
+    gr.on(
+        triggers=[input_text.submit, btn.click],
+        fn=run_t2tt,
+        inputs=[input_text, source_language, target_language],
+        outputs=output_text,
+        api_name="t2tt",
+    )
+
+with gr.Blocks() as demo_asr:
+    with gr.Row():
+        with gr.Column():
+            with gr.Group():
+                input_audio = gr.Audio(label="Input speech", type="filepath")
+                target_language = gr.Dropdown(
+                    label="Target language",
+                    choices=ASR_TARGET_LANGUAGE_NAMES,
+                    value=DEFAULT_TARGET_LANGUAGE,
+                )
+            btn = gr.Button("Translate")
+        with gr.Column():
+            output_text = gr.Textbox(label="Translated text")
+
+    gr.Examples(
+        examples=[],
+        inputs=[input_audio, target_language],
+        outputs=output_text,
+        fn=run_asr,
+        cache_examples=CACHE_EXAMPLES,
+        api_name=False,
+    )
+
+    btn.click(
+        fn=run_asr,
+        inputs=[input_audio, target_language],
+        outputs=output_text,
+        api_name="asr",
+    )
+
+
+with gr.Blocks(css="style.css") as demo:
+    gr.Markdown(DESCRIPTION)
+    gr.DuplicateButton(
+        value="Duplicate Space for private use",
+        elem_id="duplicate-button",
+        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
+    )
+
+    with gr.Tabs():
+        with gr.Tab(label="S2ST"):
+            demo_s2st.render()
+        with gr.Tab(label="S2TT"):
+            demo_s2tt.render()
+        with gr.Tab(label="T2ST"):
+            demo_t2st.render()
+        with gr.Tab(label="T2TT"):
+            demo_t2tt.render()
+        with gr.Tab(label="ASR"):
+            demo_asr.render()
+
+
+if __name__ == "__main__":
+    demo.queue(max_size=50).launch()

demo/m4tv2/lang_list.py

@@ -0,0 +1,255 @@
+# Language dict
+language_code_to_name = {
+    "afr": "Afrikaans",
+    "amh": "Amharic",
+    "arb": "Modern Standard Arabic",
+    "ary": "Moroccan Arabic",
+    "arz": "Egyptian Arabic",
+    "asm": "Assamese",
+    "ast": "Asturian",
+    "azj": "North Azerbaijani",
+    "bel": "Belarusian",
+    "ben": "Bengali",
+    "bos": "Bosnian",
+    "bul": "Bulgarian",
+    "cat": "Catalan",
+    "ceb": "Cebuano",
+    "ces": "Czech",
+    "ckb": "Central Kurdish",
+    "cmn": "Mandarin Chinese",
+    "cym": "Welsh",
+    "dan": "Danish",
+    "deu": "German",
+    "ell": "Greek",
+    "eng": "English",
+    "est": "Estonian",
+    "eus": "Basque",
+    "fin": "Finnish",
+    "fra": "French",
+    "gaz": "West Central Oromo",
+    "gle": "Irish",
+    "glg": "Galician",
+    "guj": "Gujarati",
+    "heb": "Hebrew",
+    "hin": "Hindi",
+    "hrv": "Croatian",
+    "hun": "Hungarian",
+    "hye": "Armenian",
+    "ibo": "Igbo",
+    "ind": "Indonesian",
+    "isl": "Icelandic",
+    "ita": "Italian",
+    "jav": "Javanese",
+    "jpn": "Japanese",
+    "kam": "Kamba",
+    "kan": "Kannada",
+    "kat": "Georgian",
+    "kaz": "Kazakh",
+    "kea": "Kabuverdianu",
+    "khk": "Halh Mongolian",
+    "khm": "Khmer",
+    "kir": "Kyrgyz",
+    "kor": "Korean",
+    "lao": "Lao",
+    "lit": "Lithuanian",
+    "ltz": "Luxembourgish",
+    "lug": "Ganda",
+    "luo": "Luo",
+    "lvs": "Standard Latvian",
+    "mai": "Maithili",
+    "mal": "Malayalam",
+    "mar": "Marathi",
+    "mkd": "Macedonian",
+    "mlt": "Maltese",
+    "mni": "Meitei",
+    "mya": "Burmese",
+    "nld": "Dutch",
+    "nno": "Norwegian Nynorsk",
+    "nob": "Norwegian Bokm\u00e5l",
+    "npi": "Nepali",
+    "nya": "Nyanja",
+    "oci": "Occitan",
+    "ory": "Odia",
+    "pan": "Punjabi",
+    "pbt": "Southern Pashto",
+    "pes": "Western Persian",
+    "pol": "Polish",
+    "por": "Portuguese",
+    "ron": "Romanian",
+    "rus": "Russian",
+    "slk": "Slovak",
+    "slv": "Slovenian",
+    "sna": "Shona",
+    "snd": "Sindhi",
+    "som": "Somali",
+    "spa": "Spanish",
+    "srp": "Serbian",
+    "swe": "Swedish",
+    "swh": "Swahili",
+    "tam": "Tamil",
+    "tel": "Telugu",
+    "tgk": "Tajik",
+    "tgl": "Tagalog",
+    "tha": "Thai",
+    "tur": "Turkish",
+    "ukr": "Ukrainian",
+    "urd": "Urdu",
+    "uzn": "Northern Uzbek",
+    "vie": "Vietnamese",
+    "xho": "Xhosa",
+    "yor": "Yoruba",
+    "yue": "Cantonese",
+    "zlm": "Colloquial Malay",
+    "zsm": "Standard Malay",
+    "zul": "Zulu",
+}
+LANGUAGE_NAME_TO_CODE = {v: k for k, v in language_code_to_name.items()}
+
+# Source langs: S2ST / S2TT / ASR don't need source lang
+# T2TT / T2ST use this
+text_source_language_codes = [
+    "afr",
+    "amh",
+    "arb",
+    "ary",
+    "arz",
+    "asm",
+    "azj",
+    "bel",
+    "ben",
+    "bos",
+    "bul",
+    "cat",
+    "ceb",
+    "ces",
+    "ckb",
+    "cmn",
+    "cym",
+    "dan",
+    "deu",
+    "ell",
+    "eng",
+    "est",
+    "eus",
+    "fin",
+    "fra",
+    "gaz",
+    "gle",
+    "glg",
+    "guj",
+    "heb",
+    "hin",
+    "hrv",
+    "hun",
+    "hye",
+    "ibo",
+    "ind",
+    "isl",
+    "ita",
+    "jav",
+    "jpn",
+    "kan",
+    "kat",
+    "kaz",
+    "khk",
+    "khm",
+    "kir",
+    "kor",
+    "lao",
+    "lit",
+    "lug",
+    "luo",
+    "lvs",
+    "mai",
+    "mal",
+    "mar",
+    "mkd",
+    "mlt",
+    "mni",
+    "mya",
+    "nld",
+    "nno",
+    "nob",
+    "npi",
+    "nya",
+    "ory",
+    "pan",
+    "pbt",
+    "pes",
+    "pol",
+    "por",
+    "ron",
+    "rus",
+    "slk",
+    "slv",
+    "sna",
+    "snd",
+    "som",
+    "spa",
+    "srp",
+    "swe",
+    "swh",
+    "tam",
+    "tel",
+    "tgk",
+    "tgl",
+    "tha",
+    "tur",
+    "ukr",
+    "urd",
+    "uzn",
+    "vie",
+    "yor",
+    "yue",
+    "zsm",
+    "zul",
+]
+TEXT_SOURCE_LANGUAGE_NAMES = sorted([language_code_to_name[code] for code in text_source_language_codes])
+
+# Target langs:
+# S2ST / T2ST
+s2st_target_language_codes = [
+    "eng",
+    "arb",
+    "ben",
+    "cat",
+    "ces",
+    "cmn",
+    "cym",
+    "dan",
+    "deu",
+    "est",
+    "fin",
+    "fra",
+    "hin",
+    "ind",
+    "ita",
+    "jpn",
+    "kor",
+    "mlt",
+    "nld",
+    "pes",
+    "pol",
+    "por",
+    "ron",
+    "rus",
+    "slk",
+    "spa",
+    "swe",
+    "swh",
+    "tel",
+    "tgl",
+    "tha",
+    "tur",
+    "ukr",
+    "urd",
+    "uzn",
+    "vie",
+]
+S2ST_TARGET_LANGUAGE_NAMES = sorted([language_code_to_name[code] for code in s2st_target_language_codes])
+T2ST_TARGET_LANGUAGE_NAMES = S2ST_TARGET_LANGUAGE_NAMES
+
+# S2TT / T2TT / ASR
+S2TT_TARGET_LANGUAGE_NAMES = TEXT_SOURCE_LANGUAGE_NAMES
+T2TT_TARGET_LANGUAGE_NAMES = TEXT_SOURCE_LANGUAGE_NAMES
+ASR_TARGET_LANGUAGE_NAMES = TEXT_SOURCE_LANGUAGE_NAMES

demo/m4tv2/requirements.txt

@@ -0,0 +1,5 @@
+gradio~=4.5.0
+omegaconf~=2.3.0
+torch~=2.1.0
+torchaudio~=2.1.0
+fairseq2~=0.2.0

docs/expressive/seamless_align_expressive_README

@@ -0,0 +1,27 @@
+# SeamlessAlignExpressive
+
+Building upon our past work with WikiMatrix, CCMatrix, NLLB, SpeechMatrix and SeamlessM4T, we’re introducing the first expressive speech alignment procedure. Starting with raw data, the expressive alignment procedure automatically discovers pairs of audio segments sharing not only the same meaning, but the same overall expressivity. To showcase this procedure, we are making metadata available to create a benchmarking dataset called SeamlessAlignExpressive, that can be used to validate the quality of our alignment method. SeamlessAlignExpressive is the first large-scale collection of multilingual audio alignments for expressive translation for benchmarking.
+
+## Format
+
+The metadata files are space separated, gzip files. Each file corresponds to one alignment direction. File naming convention: we use 2 letters with an 'A': e.g. `frA`, `enA`, `deA`.
+
+For example, the direction `deA-enA` corresponds to information for reconstructing German speech to English speech alignments.
+
+Each line has 9 columns.
+
+The columns correspond to:
+    - `direction`: direction, e.g. `enA-deA`
+    - `side`: side, e.g. `enA` or `deA`
+    - `line_no`: alignment number
+    - `cc_warc`: The public CC warc file reference containing the public audio url
+    - `duration`: original file duration
+    - `audio_speech_segment_url`: public audio reference
+    - `audio_speech_start_frame`: start frame when the audio is resampled at 16kHz
+    - `audio_speech_end_frame`: end frame when the audio is resampled at 16kHz
+    - `laser_score`: score of the alignment
+
+
+## Data
+
+[deA-enA](https://dl.fbaipublicfiles.com/seamless/data/seamless_align_expressive/seamless.dataset.metadata.public.deA-enA.tsv.gz) [enA-esA](https://dl.fbaipublicfiles.com/seamless/data/seamless_align_expressive/seamless.dataset.metadata.public.enA-esA.tsv.gz) [enA-frA](https://dl.fbaipublicfiles.com/seamless/data/seamless_align_expressive/seamless.dataset.metadata.public.enA-frA.tsv.gz) [enA-itA](https://dl.fbaipublicfiles.com/seamless/data/seamless_align_expressive/seamless.dataset.metadata.public.enA-itA.tsv.gz) [enA-zhA](https://dl.fbaipublicfiles.com/seamless/data/seamless_align_expressive/seamless.dataset.metadata.public.enA-zhA.tsv.gz)

ggml/examples/unity/model_loader.cpp

@@ -137,6 +137,7 @@ void model_loader::load_vocab(llama_vocab& vocab, std::ifstream &fin)
 
     std::string packed_vocab = get_name(fin);
     std::int64_t ctx_size = vocab_size * sizeof(float) + vocab_size + 2 * ggml_tensor_overhead();
+    ctx_size *= 2;
     ggml_context* ctx = ggml_init(ggml_init_params{ctx_size, nullptr, false});
     ggml_tensor* lengths_tensor = load_tensor_value(fin, ctx);
     std::int8_t* lengths = (std::int8_t*)lengths_tensor->data;

ggml/examples/unity/model_loader.h

@@ -2,7 +2,7 @@
 // All rights reserved.
 //
 // This source code is licensed under the license found in the
-// LICENSE file in the root directory of this source tree.
+// MIT_LICENSE file in the root directory of this source tree.
 
 #pragma once
 

ggml/examples/unity/unity.cpp

@@ -133,9 +133,13 @@ int main(int argc, char ** argv) {
         fprintf(stderr, "%s: failed to load model from '%s'\n", __func__, params.model.c_str());
         return 1;
     }
+    int ctx_size_gb = 20;
+    if (model.hparams["w2v2_encoder_config__num_encoder_layers"] == 24) {
+        ctx_size_gb = 40;
+    } 
 
     char result_str[4096];
-    static std::vector<uint8_t> encoder_buf(20 * 1024LL * 1024LL * 1024LL);
+    static std::vector<uint8_t> encoder_buf(ctx_size_gb * 1024LL * 1024LL * 1024LL);
 
     std::string input;
     bool interactive = params.files.size() == 0;

ggml/ggml_convert.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import dataclasses
 import logging

ggml/include/ggml/ggml.h

@@ -214,7 +214,7 @@
 #define GGML_QNT_VERSION_FACTOR 1000 // do not change this
 
 #define GGML_MAX_DIMS          4
-#define GGML_MAX_NODES         4096
+#define GGML_MAX_NODES         8192
 #define GGML_MAX_PARAMS        256
 #define GGML_MAX_CONTEXTS      64
 #define GGML_MAX_SRC           6
@@ -530,7 +530,7 @@ extern "C" {
     // next prime after GGML_MAX_NODES
     // #define GGML_GRAPH_HASHTABLE_SIZE 4099
     // next prime after GGML_MAX_NODES * 2 (nodes + leafs)
-    #define GGML_GRAPH_HASHTABLE_SIZE 8273
+    #define GGML_GRAPH_HASHTABLE_SIZE 16411
 
     // computation graph
     struct ggml_cgraph {

ggml/test_unity_cpp.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import ctypes
 import functools

setup.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from setuptools import find_packages, setup
 

src/seamless_communication/__init__.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from pathlib import Path
 

src/seamless_communication/cards/expresso.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: expresso
 uri: "https://dl.fbaipublicfiles.com/textless_nlp/expresso/data/expresso.tar"

src/seamless_communication/cards/mexpresso_text.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: mexpresso_text
 uri: "https://dl.fbaipublicfiles.com/seamless/datasets/mexpresso_text/mexpresso_text.tar"

src/seamless_communication/cards/mintox.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: mintox
 model_name: MinTox

src/seamless_communication/cards/nar_t2u_aligner.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: nar_t2u_aligner
 char_tokenizer: "https://dl.fbaipublicfiles.com/seamless/models/spm_char_lang38_tc.model"

src/seamless_communication/cards/seamlessM4T_large.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: seamlessM4T_large
 base: unity_nllb-100

src/seamless_communication/cards/seamlessM4T_medium.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: seamlessM4T_medium
 base: unity_nllb-200

src/seamless_communication/cards/seamlessM4T_v2_large.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: seamlessM4T_v2_large
 base: unity_nllb-100

src/seamless_communication/cards/seamless_expressivity.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: seamless_expressivity
 base: unity_nllb-100

src/seamless_communication/cards/seamless_streaming_monotonic_decoder.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: seamless_streaming_monotonic_decoder
 model_type: monotonic_decoder

src/seamless_communication/cards/seamless_streaming_unity.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: seamless_streaming_unity
 base: unity_nllb-100

src/seamless_communication/cards/unity_nllb-100.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: unity_nllb-100
 model_type: unity

src/seamless_communication/cards/unity_nllb-200.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: unity_nllb-200
 model_type: unity

src/seamless_communication/cards/vocoder_36langs.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: vocoder_36langs
 model_type: vocoder_code_hifigan

src/seamless_communication/cards/vocoder_pretssel.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: vocoder_pretssel
 model_type: vocoder_pretssel

src/seamless_communication/cards/vocoder_pretssel_16khz.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: vocoder_pretssel_16khz
 model_type: vocoder_pretssel

src/seamless_communication/cards/vocoder_v2.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: vocoder_v2
 model_type: vocoder_code_hifigan

src/seamless_communication/cards/xlsr2_1b_v2.yaml

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 name: xlsr2_1b_v2
 model_type: wav2vec2

src/seamless_communication/cli/__init__.py

@@ -2,4 +2,4 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.

src/seamless_communication/cli/eval_utils/__init__.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 
 from seamless_communication.cli.eval_utils.compute_metrics import (

src/seamless_communication/cli/eval_utils/compute_metrics.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import json
 import logging

src/seamless_communication/cli/eval_utils/lang_mapping.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 LANG2_LANG3 = {
     "en": "eng",

src/seamless_communication/cli/expressivity/data/prepare_mexpresso.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 """
 Script to create mExpresso Eng-XXX S2T dataset.

src/seamless_communication/cli/expressivity/evaluate/post_process_pauserate.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import pandas as pd
 import csv

src/seamless_communication/cli/expressivity/evaluate/pretssel_inference.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import argparse
 import contextlib

src/seamless_communication/cli/expressivity/evaluate/pretssel_inference_helper.py

@@ -1,7 +1,7 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 # All rights reserved.
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import List
 

src/seamless_communication/cli/expressivity/evaluate/run_asr_bleu.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from fire import Fire
 import pandas as pd

src/seamless_communication/cli/m4t/audio_to_units/__init__.py

@@ -2,4 +2,4 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.

src/seamless_communication/cli/m4t/audio_to_units/audio_to_units.py

@@ -1,7 +1,7 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import argparse
 import logging

src/seamless_communication/cli/m4t/evaluate/__init__.py

@@ -2,4 +2,4 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.

src/seamless_communication/cli/m4t/evaluate/evaluate.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import argparse
 import contextlib

src/seamless_communication/cli/m4t/finetune/__init__.py

@@ -2,4 +2,4 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.

src/seamless_communication/cli/m4t/finetune/dataloader.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 
 import json

src/seamless_communication/cli/m4t/finetune/dataset.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 
 import argparse

src/seamless_communication/cli/m4t/finetune/dist_utils.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 
 import logging

src/seamless_communication/cli/m4t/finetune/finetune.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import argparse
 import logging

src/seamless_communication/cli/m4t/finetune/trainer.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 
 import logging

src/seamless_communication/cli/m4t/predict/__init__.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from seamless_communication.cli.m4t.predict.predict import (
     add_inference_arguments as add_inference_arguments,

src/seamless_communication/cli/m4t/predict/predict.py

@@ -1,7 +1,7 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import argparse
 import logging

src/seamless_communication/cli/streaming/__init__.py

@@ -2,4 +2,4 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.

src/seamless_communication/cli/streaming/evaluate.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import argparse
 import logging

src/seamless_communication/cli/streaming/scorers/__init__.py

@@ -2,4 +2,4 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.

src/seamless_communication/cli/streaming/scorers/seamless_quality_scorer.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from __future__ import annotations
 

src/seamless_communication/cli/toxicity/asr_etox.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import argparse
 import tempfile

src/seamless_communication/cli/toxicity/etox.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import argparse
 import sys

src/seamless_communication/datasets/__init__.py

@@ -2,4 +2,4 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.

src/seamless_communication/datasets/datatypes.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 
 from dataclasses import dataclass

src/seamless_communication/datasets/huggingface.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 
 import logging

src/seamless_communication/inference/__init__.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from seamless_communication.inference.generator import (
     SequenceGeneratorOptions as SequenceGeneratorOptions,

src/seamless_communication/inference/generator.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from dataclasses import dataclass
 from typing import List, Optional, Tuple

src/seamless_communication/inference/translator.py

@@ -1,7 +1,7 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 # All rights reserved.
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import logging
 from dataclasses import dataclass

src/seamless_communication/models/__init__.py

@@ -2,4 +2,4 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.

src/seamless_communication/models/aligner/__init__.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from seamless_communication.models.aligner.model import (
     UnitY2AlignmentEncoder as UnitY2AlignmentEncoder,

src/seamless_communication/models/aligner/alignment_extractor.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import os
 from typing import Any, List, Tuple, Union

src/seamless_communication/models/aligner/builder.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from dataclasses import dataclass
 from typing import Optional, Union

src/seamless_communication/models/aligner/loader.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import Any, List, Mapping
 

src/seamless_communication/models/aligner/model.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import Any, List, Tuple, Union
 

src/seamless_communication/models/generator/__init__.py

@@ -2,4 +2,4 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.

src/seamless_communication/models/generator/builder.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from dataclasses import dataclass
 from typing import Any, Dict, List, Literal, Optional, Tuple

src/seamless_communication/models/generator/ecapa_tdnn.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import List, Optional, Tuple
 

src/seamless_communication/models/generator/ecapa_tdnn_builder.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from dataclasses import dataclass
 from typing import List, Optional

src/seamless_communication/models/generator/loader.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 
 from typing import Any, Mapping

src/seamless_communication/models/generator/streamable.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import math
 import warnings

src/seamless_communication/models/generator/vocoder.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import Any, Dict, List, Literal, Optional, Tuple
 

src/seamless_communication/models/monotonic_decoder/__init__.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 from seamless_communication.models.monotonic_decoder.builder import (
     MonotonicDecoderBuilder as MonotonicDecoderBuilder,
 )

src/seamless_communication/models/monotonic_decoder/builder.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from dataclasses import dataclass
 from typing import Optional

src/seamless_communication/models/monotonic_decoder/loader.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import Any, Mapping
 

src/seamless_communication/models/monotonic_decoder/model.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import Optional, Tuple, final
 

src/seamless_communication/models/monotonic_decoder/monotonic_decoder.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import Iterable, List, Optional, Tuple, final
 

src/seamless_communication/models/monotonic_decoder/monotonic_decoder_layer.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import Optional, Tuple, final
 

src/seamless_communication/models/monotonic_decoder/p_choose.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import Optional, final
 

src/seamless_communication/models/pretssel/__init__.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from seamless_communication.models.pretssel.ecapa_tdnn import ECAPA_TDNN as ECAPA_TDNN
 from seamless_communication.models.pretssel.ecapa_tdnn_builder import (

src/seamless_communication/models/pretssel/ecapa_tdnn.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import List, Optional, Tuple
 

src/seamless_communication/models/pretssel/ecapa_tdnn_builder.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from dataclasses import dataclass
 from typing import List, Optional

src/seamless_communication/models/tokenizer.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from typing import Optional, Sequence, Set, final
 

src/seamless_communication/models/unit_extractor/__init__.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 from seamless_communication.models.unit_extractor.kmeans import (
     KmeansModel as KmeansModel,

src/seamless_communication/models/unit_extractor/kmeans.py

@@ -2,7 +2,7 @@
 # All rights reserved.
 #
 # This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
+# MIT_LICENSE file in the root directory of this source tree.
 
 import numpy as np
 import torch