婴儿哭声验证 - 在CryCeleb2023数据上微调的ECAPA-TDNN模型

这个模型是SpeechBrain ECAPA-TDNN在 CryCeleb dataset 数据上进行微调的。

训练可以使用 SpeechBrain recipe available on Github 进行复现。

它可以作为 CryCeleb2023 challenge 的基准。

参考资料

模型和数据集说明

@article{ubenwa2023cryceleb,
      title={CryCeleb: A Speaker Verification Dataset Based on Infant Cry Sounds}, 
      author={David Budaghyan and Arsenii Gorin and Cem Subakan and Charles C. Onu},
      year={2023},
      journal={preprint arXiv:2305.00969},
}

ECAPA-TDNN

@inproceedings{DBLP:conf/interspeech/DesplanquesTD20,
  author    = {Brecht Desplanques and
               Jenthe Thienpondt and
               Kris Demuynck},
  editor    = {Helen Meng and
               Bo Xu and
               Thomas Fang Zheng},
  title     = {{ECAPA-TDNN:} Emphasized Channel Attention, Propagation and Aggregation
               in {TDNN} Based Speaker Verification},
  booktitle = {Interspeech 2020},
  pages     = {3830--3834},
  publisher = {{ISCA}},
  year      = {2020},
}

SpeechBrain

@misc{speechbrain,
  title={{SpeechBrain}: A General-Purpose Speech Toolkit},
  author={Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and François Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio},
  year={2021},
  eprint={2106.04624},
  archivePrefix={arXiv},
  primaryClass={eess.AS},
  note={arXiv:2106.04624}
}