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facebook/
seamless-streaming

seamless_communication

audio-to-audio

text-to-speech

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SeamlessStreaming

SeamlessStreaming is a multilingual streaming translation model. It supports:

Streaming Automatic Speech Recognition on 96 languages.
Simultaneous translation on 101 source languages for speech input.
Simultaneous translation on 96 target languages for text output.
Simultaneous translation on 36 target languages for speech output.

SeamlessStreaming models

Model Name	#params	checkpoint	metrics
SeamlessStreaming	2.5B	🤗 Model card - monotonic decoder checkpoint - streaming UnitY2 checkpoint	metrics

The evaluation data ids for FLEURS, CoVoST2 and CVSS-C can be found here

Evaluating SeamlessStreaming models

To reproduce our results, or to evaluate using the same metrics over your own test sets, please check out the Evaluation README here. Streaming evaluation depends on the SimulEval library.

Seamless Streaming demo

Running on HF spaces

You can simply duplicate the space to run it. 🤗 HF Space

Running locally

Install backend seamless_server dependencies

[!NOTE] Please note: we do not recommend running the model on CPU. CPU inference will be slow and introduce noticable delays in the simultaneous translation.

[!NOTE] The example below is for PyTorch stable (2.1.1) and variant cu118. Check here to find the torch/torchaudio command for your variant. Check here to find the fairseq2 command for your variant.

If running for the first time, create conda environment and install the desired torch version. Then install the rest of the requirements:

cd seamless_server
conda create --yes --name smlss_server python=3.8 libsndfile==1.0.31
conda activate smlss_server
conda install --yes pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
pip install fairseq2 --pre --extra-index-url https://fair.pkg.atmeta.com/fairseq2/whl/nightly/pt2.1.1/cu118
pip install -r requirements.txt

Install frontend streaming-react-app dependencies

conda install -c conda-forge nodejs
cd streaming-react-app
npm install --global yarn
yarn
yarn build  # this will create the dist/ folder

Running the server

The server can be run locally with uvicorn below. Run the server in dev mode:

cd seamless_server
uvicorn app_pubsub:app --reload --host localhost

Run the server in prod mode:

cd seamless_server
uvicorn app_pubsub:app --host 0.0.0.0

To enable additional logging from uvicorn pass --log-level debug or --log-level trace.

Debuging

If you enable "Server Debug Flag" when starting streaming from the client, this enables extensive debug logging and it saves audio files in /debug folder.

Citation

For EMMA, please cite :

bibtex

@article{ma_efficient_2023,
  author={Ma, Xutai and Sun, Anna and Ouyang, Siqi and Inaguma, Hirofumi and Tomasello, Paden},
  title={Efficient Monotonic Multihead Attention},
  year={2023},
  url={https://ai.meta.com/research/publications/efficient-monotonic-multihead-attention/},
}

For SeamlessStreaming, please cite :