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PENG, J. STAFYLAKIS, T. GU, R. PLCHOT, O. MOŠNER, L. BURGET, L. ČERNOCKÝ, J.
Originální název
Parameter-Efficient Transfer Learning of Pre-Trained Transformer Models for Speaker Verification Using Adapters
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Recently, the pre-trained Transformer models have received a rising interest in the field of speech processing thanks to their great success in various downstream tasks. However, most fine-tuning approaches update all the parameters of the pre-trained model, which becomes prohibitive as the model size grows and sometimes results in over- fitting on small datasets. In this paper, we conduct a comprehensive analysis of applying parameter-efficient transfer learning (PETL) methods to reduce the required learnable parameters for adapting to speaker verification tasks. Specifically, during the fine-tuning process, the pre-trained models are frozen, and only lightweight modules inserted in each Transformer block are trainable (a method known as adapters). Moreover, to boost the performance in a cross- language low-resource scenario, the Transformer model is further tuned on a large intermediate dataset before directly fine-tuning it on a small dataset. With updating fewer than 4% of parameters, (our proposed) PETL-based methods achieve comparable performances with full fine-tuning methods (Vox1-O: 0.55%, Vox1-E: 0.82%, Vox1-H:1.73%).
Klíčová slova
Speaker verification, pre-trained model, adapter, fine-tuning, transfer learning
Autoři
PENG, J.; STAFYLAKIS, T.; GU, R.; PLCHOT, O.; MOŠNER, L.; BURGET, L.; ČERNOCKÝ, J.
Vydáno
4. 6. 2023
Nakladatel
IEEE Signal Processing Society
Místo
Rhodes Island
ISBN
978-1-7281-6327-7
Kniha
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Strany od
1
Strany do
5
Strany počet
URL
https://ieeexplore.ieee.org/document/10094795
BibTex
@inproceedings{BUT185200, author="PENG, J. and STAFYLAKIS, T. and GU, R. and PLCHOT, O. and MOŠNER, L. and BURGET, L. and ČERNOCKÝ, J.", title="Parameter-Efficient Transfer Learning of Pre-Trained Transformer Models for Speaker Verification Using Adapters", booktitle="ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings", year="2023", pages="1--5", publisher="IEEE Signal Processing Society", address="Rhodes Island", doi="10.1109/ICASSP49357.2023.10094795", isbn="978-1-7281-6327-7", url="https://ieeexplore.ieee.org/document/10094795" }