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README.md
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license: unknown
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license: unknown
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---
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# Seamless Streaming
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It is the streaming only model and Seamless is the expressive streaming model.
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## Quick start:
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Evaluation can be run with the `streaming_evaluate` CLI.
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We use the `seamless_streaming_unity` for loading the speech encoder and T2U models, and `seamless_streaming_monotonic_decoder` for loading the text decoder for streaming evaluation. This is already set as defaults for the `streaming_evaluate` CLI, but can be overridden using the `--unity-model-name` and `--monotonic-decoder-model-name` args if required.
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Note that the numbers in our paper use single precision floating point format (fp32) for evaluation by setting `--dtype fp32`. Also note that the results from running these evaluations might be slightly different from the results reported in our paper (which will be updated soon with the new results).
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### S2TT:
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Set the task to `s2tt` for evaluating the speech-to-text translation part of the SeamlessStreaming model.
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```bash
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streaming_evaluate --task s2tt --data-file <path_to_data_tsv_file> --audio-root-dir <path_to_audio_root_directory> --output <path_to_evaluation_output_directory> --tgt-lang <3_letter_lang_code>
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```
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Note: The `--ref-field` can be used to specify the name of the reference column in the dataset.
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### ASR:
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Set the task to `asr` for evaluating the automatic speech recognition part of the SeamlessStreaming model. Make sure to pass the source language as the `--tgt-lang` arg.
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```bash
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streaming_evaluate --task asr --data-file <path_to_data_tsv_file> --audio-root-dir <path_to_audio_root_directory> --output <path_to_evaluation_output_directory> --tgt-lang <3_letter_source_lang_code>
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```
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### S2ST:
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#### SeamlessStreaming:
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Set the task to `s2st` for evaluating the speech-to-speech translation part of the SeamlessStreaming model.
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```bash
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streaming_evaluate --task s2st --data-file <path_to_data_tsv_file> --audio-root-dir <path_to_audio_root_directory> --output <path_to_evaluation_output_directory> --tgt-lang <3_letter_lang_code>
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```
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#### Seamless:
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The Seamless model is an unified model for streaming expressive speech-to-speech tranlsation. Use the `--expressive` arg for running evaluation of this unified model.
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```bash
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streaming_evaluate --task s2st --data-file <path_to_data_tsv_file> --audio-root-dir <path_to_audio_root_directory> --output <path_to_evaluation_output_directory> --tgt-lang <3_letter_lang_code> --expressive
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```
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Note: In the current version of our paper, we use vocoder_pretssel_16khz for the evaluation , so in order to reproduce those results please add this arg to the above command: `--vocoder-name vocoder_pretssel_16khz`
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