AudioVisualLip
Audio-Visual Voice Biometrics is a audio-visual speaker recognition task, which leverages auditory and visual speech in a video. The portrait- and linguistic-based speaker characteristics are extracted via the temporal dynamics modeling. It involves the conventional speaker recognition and lip biometrics tasks.
Introduction
This is the official implementation of ICASSP23 paper CROSS-MODAL AUDIO-VISUAL CO-LEARNING FOR TEXT-INDEPENDENT SPEAKER VERIFICATION.
Datasets
Results
Reference
AVLip:
@inproceedings{liu2023cross,
title={Cross-Modal Audio-Visual Co-Learning for Text-Independent Speaker Verification},
author={Liu, Meng and Lee, Kong Aik and Wang, Longbiao and Zhang, Hanyi and Zeng, Chang and Dang, Jianwu},
booktitle={ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={1--5},
year={2023},
organization={IEEE}
}
DeepLip:
@inproceedings{liu2021deeplip,
title={DeepLip: A Benchmark for Deep Learning-Based Audio-Visual Lip Biometrics},
author={Liu, Meng and Wang, Longbiao and Lee, Kong Aik and Zhang, Hanyi and Zeng, Chang and Dang, Jianwu},
booktitle={2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)},
pages={122--129},
year={2021},
organization={IEEE}
}