Speaker recognition model with robust front-end processing algorithm

Yingzi Lian; Jing Pang

doi:10.1117/12.2639261

15 July 2022 Speaker recognition model with robust front-end processing algorithm

Yingzi Lian, Jing Pang

Proceedings Volume 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022); 122580T (2022) https://doi.org/10.1117/12.2639261
Event: International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 2022, Qingdao, China

Abstract

The end-to-end speaker recognition model has made a great breakthrough in the research field and practical application scenarios. However, in practical application, we often suffer the diversity of noise, and the interference of noise will affect the performance of speaker recognition and classification model, and the model usually degrades in unseen scenes with noise. In this paper, a speaker recognition model combined with front-end enhancement is proposed. The front-end enhancement model (DTLN or CRNN) is combined with the back-end speaker recognition model (Res2Net-GhostVLAD) to improve the robustness of the model against noisy scenes, and the generalization capability of the model is increased by the data augmentation method (SpecAugment). Our proposed method was trained on VoxCeleb and AISHELL datasets and tested on VoxCeleb datasets. The test results show that the proposed method significantly improves the performance of the speaker recognition model in noisy scenarios, and the relative improvement of different front-end models is 9% and 13%, respectively.

Citation Download Citation

Yingzi Lian and Jing Pang "Speaker recognition model with robust front-end processing algorithm", Proc. SPIE 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 122580T (15 July 2022); https://doi.org/10.1117/12.2639261

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KEYWORDS

Data modeling

Denoising

Speaker recognition

Performance modeling

Signal processing

Feature extraction

Detection and tracking algorithms

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