Owsm V3.1 Ebf

🚀 OWSM: Open Whisper-style Speech Model

OWSM aims to develop fully open speech foundation models using publicly available data and open-source toolkits, including ESPnet. It provides solutions for various speech - related tasks, offering high - performance and accessible speech processing capabilities.

Inference examples can be found on our project page. Our demo is available here.

OWSM v3.1 is an improved version of OWSM v3. It significantly outperforms OWSM v3 in almost all evaluation benchmarks. We do not include any new training data. Instead, we utilize a state - of - the - art speech encoder, E - Branchformer.

The model in this repo has 1.02B parameters in total and is trained on 180k hours of public speech data. Specifically, it supports the following speech - to - text tasks:

• Speech recognition
• Any - to - any - language speech translation
• Utterance - level alignment
• Long - form transcription
• Language identification

📚 Documentation

Model Information

📄 License

The model is released under the cc - by - 4.0 license.

📚 Citations

OWSM - CTC

@inproceedings{owsm-ctc,
    title = "{OWSM}-{CTC}: An Open Encoder-Only Speech Foundation Model for Speech Recognition, Translation, and Language Identification",
    author = "Peng, Yifan  and
      Sudo, Yui  and
      Shakeel, Muhammad  and
      Watanabe, Shinji",
    booktitle = "Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)",
    year = "2024",
    month= {8},
    url = "https://aclanthology.org/2024.acl-long.549",
}

OWSM v3.1 and v3.2

@inproceedings{owsm-v32,
  title={On the Effects of Heterogeneous Data Sources on Speech-to-Text Foundation Models},
  author={Jinchuan Tian and Yifan Peng and William Chen and Kwanghee Choi and Karen Livescu and Shinji Watanabe},
  booktitle={Proceedings of the Annual Conference of the International Speech Communication Association (INTERSPEECH)},
  year={2024},
  month={9},
  pdf="https://arxiv.org/pdf/2406.09282"
}
@inproceedings{owsm-v31,
  title={{OWSM v3.1: Better and Faster Open Whisper-Style Speech Models based on E-Branchformer}},
  author={Yifan Peng and Jinchuan Tian and William Chen and Siddhant Arora and Brian Yan and Yui Sudo and Muhammad Shakeel and Kwanghee Choi and Jiatong Shi and Xuankai Chang and Jee-weon Jung and Shinji Watanabe},
  booktitle={Proceedings of the Annual Conference of the International Speech Communication Association (INTERSPEECH)},
  year={2024},
  month={9},
  pdf="https://arxiv.org/pdf/2401.16658",
}

Initial OWSM (v1, v2, v3)

@inproceedings{owsm,
  title={Reproducing Whisper-Style Training Using An Open-Source Toolkit And Publicly Available Data},
  author={Yifan Peng and Jinchuan Tian and Brian Yan and Dan Berrebbi and Xuankai Chang and Xinjian Li and Jiatong Shi and Siddhant Arora and William Chen and Roshan Sharma and Wangyou Zhang and Yui Sudo and Muhammad Shakeel and Jee-weon Jung and Soumi Maiti and Shinji Watanabe},
  booktitle={Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)},
  year={2023},
  month={12},
  pdf="https://arxiv.org/pdf/2309.13876",
}