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UniSpeech-SAT

UniSpeech-SAT (ICASSP 2022 Submission): Universal Speech Representation Learning with Speaker Aware Pre-Training

Universal Representation Evaluation on SUPERB

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Downstream Task Performance

We also evaluate our models on typical speaker related benchmarks.

Speaker Verification

Model Fix pre-train Vox1-O Vox1-E Vox1-H
ECAPA-TDNN - 0.87 1.12 2.12
HuBERT large Yes 0.888 0.912 1.853
Wav2Vec2.0 (XLSR) Yes 0.915 0.945 1.895
UniSpeech-SAT large Yes 0.771 0.781 1.669
HuBERT large No 0.585 0.654 1.342
Wav2Vec2.0 (XLSR) No 0.564 0.605 1.23
UniSpeech-SAT large No 0.564 0.561 1.23

Our paper for verification

Speech Separation

Evaluation on LibriCSS

Model 0S 0L OV10 OV20 OV30 OV40
Conformer (SOTA) 4.5 4.4 6.2 8.5 11 12.6
HuBERT base 4.7 4.6 6.1 7.9 10.6 12.3
UniSpeech-SAT base+ 4.4 4.4 5.4 7.2 9.2 10.5
UniSpeech-SAT large 4.3 4.2 5.0 6.3 8.2 8.8

Speaker Diarization

Evaluation on CALLHOME

Model spk_2 spk_3 spk_4 spk_5 spk_6 spk_all
EEND-vector clustering 7.96 11.93 16.38 21.21 23.1 12.49
EEND-EDA clustering (SOTA) 7.11 11.88 14.37 25.95 21.95 11.84
HuBERT base 7.93 12.07 15.21 19.59 23.32 12.63
HuBERT large 7.39 11.97 15.76 19.82 22.10 12.40
UniSpeech-SAT large 5.93 10.66 12.9 16.48 23.25 10.92

License

This project is licensed under the license found in the LICENSE file in the root directory of this source tree. Portions of the source code are based on the FAIRSEQ project.

Microsoft Open Source Code of Conduct

Reference

If you find our work is useful in your research, please cite the following paper:

@article{Chen2021UniSpeechSAT,
  title   = {UniSpeech-SAT: Universal Speech Representation Learning with  Speaker Aware Pre-Training},
  author  = {Sanyuan Chen and Yu Wu and Chengyi Wang and Zhengyang Chen and Zhuo Chen and Shujie Liu and   Jian Wu and Yao Qian and Furu Wei and Jinyu Li and  Xiangzhan Yu},
  eprint={2110.05752},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  year={2021}
}

Contact Information

For help or issues using UniSpeech models, please submit a GitHub issue.

For other communications related to UniSpeech, please contact Yu Wu ([email protected]).