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--- |
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language: "fr" |
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thumbnail: |
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tags: |
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- wav2vec2 |
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license: "apache-2.0" |
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--- |
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# LeBenchmark: wav2vec2 base model trained on 1K hours of French *female-only* speech |
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LeBenchmark provides an ensemble of pretrained wav2vec2 models on different French datasets containing spontaneous, read, and broadcasted speech. |
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For more information about our gender study for SSL moddels, please refer to our paper at: [A Study of Gender Impact in Self-supervised Models for Speech-to-Text Systems](https://arxiv.org/abs/2204.01397) |
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## Model and data descriptions |
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We release four gender-specific models trained on 1K hours of speech. |
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- [wav2vec2-FR-1K-Male-large](https://huggingface.co/LeBenchmark/wav2vec-FR-1K-Male-large/) |
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- [wav2vec2-FR-1k-Male-base](https://huggingface.co/LeBenchmark/wav2vec-FR-1K-Male-base/) |
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- [wav2vec2-FR-1K-Female-large](https://huggingface.co/LeBenchmark/wav2vec-FR-1K-Female-large/) |
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- [wav2vec2-FR-1K-Female-base](https://huggingface.co/LeBenchmark/wav2vec-FR-1K-Female-base/) |
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## Intended uses & limitations |
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Pretrained wav2vec2 models are distributed under the Apache-2.0 license. Hence, they can be reused extensively without strict limitations. However, benchmarks and data may be linked to corpora that are not completely open-sourced. |
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## Referencing our gender-specific models |
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``` |
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@inproceedings{boito22_interspeech, |
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author={Marcely Zanon Boito and Laurent Besacier and Natalia Tomashenko and Yannick Estève}, |
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title={{A Study of Gender Impact in Self-supervised Models for Speech-to-Text Systems}}, |
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year=2022, |
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booktitle={Proc. Interspeech 2022}, |
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pages={1278--1282}, |
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doi={10.21437/Interspeech.2022-353} |
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} |
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``` |
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## Referencing LeBenchmark |
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``` |
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@inproceedings{evain2021task, |
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title={Task agnostic and task specific self-supervised learning from speech with \textit{LeBenchmark}}, |
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author={Evain, Sol{\`e}ne and Nguyen, Ha and Le, Hang and Boito, Marcely Zanon and Mdhaffar, Salima and Alisamir, Sina and Tong, Ziyi and Tomashenko, Natalia and Dinarelli, Marco and Parcollet, Titouan and others}, |
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booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)}, |
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year={2021} |
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} |
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``` |
