Yifan Peng's Enhanced Speech Model 'owsm v2' in ESPnet2: Development, Evaluation, and Community Engagement Overview

This model, named owsm_v2, was developed by Yifan Peng based on the mixed_v2 recipe in ESPnet.

For an interactive experience, you can follow these steps to utilize this model within ESPnet2:

1. First, ensure that your environment is set up correctly with ESPnet version 2 and PyTorch installed.

2. Move into the ESPnet directory cd espnet and checkout commit ad7aa6c which contns recent updates for owsm_v2git checkout ad7aa6c79711948ca5ae2edbb270f9cd53e61ca9.

3. Install ESPnet locally using pip install -e .

4. Navigate to the dataset setup directory cd egs2mixed_v2s2t1 and run initialization commands to set up the environment .run.sh --skip_data_prep false --skip_trn true --download_model pyf98owsm_v2.

Evaluation

Here are some evaluation results that can help you understand the model's performance:

• Environment Detls: The current system is running Python version 3.8.16, ESPnet version as of April 2023 espnet 202304, and PyTorch version 1.10.1. The Git commit detls are provided for reference commit: ad7aa6c, date: Tue Jul 4, 2023 -0500.

Configuration

ESPnet's comprehensive documentation provides insights into the model configuration and how it can be tlored to specific needs.

Citing ESPnet

To properly cite this work, you may use either traditional citation methods or a reference from an arXiv repository:

Traditional Citation:

@inproceedingswatanabe2018espnet,

  author=Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Ruchintala and Tsubasa Ochi,

  title=ESPnet: -to- Speech Processing Toolkit,

  year=2018,

  booktitle=Proceedings of Interspeech,

  pages=2207--2211,

  doi=10.21437Interspeech.2018-1456,

  url=http:dx.doi.org10.21437Interspeech.2018-1456

arXiv Citation:

@miscwatanabe2018espnet,

  title=ESPnet: -to- Speech Processing Toolkit,

  author=Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Ruchintala and Tsubasa Ochi,

  year=2018,

  eprint=1804.00015,

  archivePrefix=arXiv,

  primaryClass=cs.CL

Usage Statistics

In the last month, there have been approximately 15 downloads of this model.

To showcase its capabilities or further engage with the community regarding potential applications and improvements, consider deploying your application to Inference API serverless on Hugging Face. The number of deployments would then be publicly visible in this section. Alternatively, for dedicated environments, you can opt for deploying to Inference points dedicated.

Community Interaction

The avlability and interaction levels in the community space espnetowsm_v2 indicate user engagement regarding this model.

This summary highlights the key detls about owsm_v2 from development through implementation within ESPnet2 to its current status, including citation guidelines and potential areas for community involvement.
This article is reproduced from: https://huggingface.co/espnet/owsm_v2

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