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P.808 Toolkit

The P.808 Toolkit is a software package that enables users to run subjective speech quality assessment test in Amazon Mechanical Turk (AMT) crowdsourcing platform, according to the ITU-T Recommendation P.808. It includes following test methods:

  • Absolute Category Rating (ACR) -- Annex A, P.808
  • Degradation Category Ratings (DCR) -- Annex B, P.808
  • Comparison Category Ratings (CCR) -- Annex C, P.808
  • Evaluating the subjective quality of speech in noise (i.e. implementation of ITU-T Rec. P.835 approach in crowdsourcing) -- Annex D, P.808

It also extends P.808 in the following ways:

  • Includes implementation of the ITU-T Rec. P.831 for the crowdsourcing approach is also provided based on the recommendations given in the ITU-T Rec. P.808.

  • NEW - Multi-dimensional Speech Quality Assessment - Following the ITU-T Rec. P.804 and extending it with reverberation, signal and overall quality.

  • NEW - Extending P.835 test to evaluate personalized noise suppression

Relevant ITU-T Recommendations are :

Technical description of the implementation and validation are given in these papers:

Citation

If you use this tool in your research please cite it with the following references:

@inproceedings{naderi2020,
  title={An Open source Implementation of ITU-T Recommendation P.808 with Validation},
  author={Naderi, Babak and Cutler, Ross},
  booktitle={Proc. INTERSPEECH},
  year={2020}
}
@inproceedings{cutler2021crowdsourcing,
  title={Crowdsourcing approach for subjective evaluation of echo impairment},
  author={Cutler, Ross and Naderi, Babak and Loide, Markus and Sootla, Sten and Saabas, Ando},
  booktitle={ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={406--410},
  year={2021},
  organization={IEEE}
}
@inproceedings{naderi2021,
  title={Subjective Evaluation of Noise Suppression Algorithms in Crowdsourcing},
  author={Naderi, Babak and Cutler, Ross},
  booktitle={Proc. INTERSPEECH},
  year={2021}
}
@inproceedings{naderi2024multi,
  title={Multi-dimensional speech quality assessment in crowdsourcing},
  author={Naderi, Babak and Cutler, Ross and Ristea, Nicolae-C{\u{a}}t{\u{a}}lin},
  booktitle={ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={696--700},
  year={2024},
  organization={IEEE}
}

Getting Started

News

++ An update with support for multi-dimensional quality assessment is published.

Troubleshooting

For bug reports and issues with this code, please see the github issues page. Please review this page before contacting the authors.

Contact

Contact Babak Naderi, Vishak Gopal or Ross Cutler with any questions.

License

Code License

MIT License

Copyright 2019 (c) Microsoft Corporation.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Audio clips License

The datasets are provided under the original terms that Microsoft received such datasets. See below for more information about each dataset.

The datasets used in this project are licensed as follows:

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.