Efficient Speech Processing Tookit for Automatic Speaker Recognition

Related tags

Deep Learning sugar
Overview

Sugar

Efficient Speech Processing Tookit for Automatic Speaker Recognition

| HuggingFace |

What's New

supernet

Requirements and Installation

  • PyTorch version >= 1.7.1
  • Python version >= 3.7.9
  • To install sugar:
git clone https://github.com/mechanicalsea/sugar.git
cd sugar
pip install --editable .

We provide pre-trained models for extracting speaker embeddings via huggingface.

Tutorials

Citing EfficientTDNN

Please, cite EfficientTDNN if you use it for your research or business.

@article{speechbrain,
  title={{EfficientTDNN}: Efficient Architecture Search for Speaker Recognition in the Wild},
  author={Rui Wang and Zhihua Wei and Haoran Duan and Shouling Ji and Zhen Hong},
  year={2021},
  eprint={2103.13581},
  archivePrefix={arXiv},
  primaryClass={eess.AS},
  note={arXiv:2103.13581}
}
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Comments
  • CVE-2007-4559 Patch

    CVE-2007-4559 Patch

    Patching CVE-2007-4559

    Hi, we are security researchers from the Advanced Research Center at Trellix. We have began a campaign to patch a widespread bug named CVE-2007-4559. CVE-2007-4559 is a 15 year old bug in the Python tarfile package. By using extract() or extractall() on a tarfile object without sanitizing input, a maliciously crafted .tar file could perform a directory path traversal attack. We found at least one unsantized extractall() in your codebase and are providing a patch for you via pull request. The patch essentially checks to see if all tarfile members will be extracted safely and throws an exception otherwise. We encourage you to use this patch or your own solution to secure against CVE-2007-4559. Further technical information about the vulnerability can be found in this blog.

    If you have further questions you may contact us through this projects lead researcher Kasimir Schulz.

    opened by TrellixVulnTeam 0
Owner
WangRui
make improvement
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