Baby cry verification with ECAPA-TDNN finetuned on CryCeleb2023 data

NOTE: this version is deprecated. Use a more accurate and reproducible updated v2 model

This model is SpeechBrain ECAPA-TDNN fine-tuned on CryCeleb dataset.

Training can be reproduced using SpeechBrain recipe available on Github.

It can be used as a baseline for CryCeleb2023 challenge.

References

Model and dataset description

@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}
}