PAS: Partial Additive Speech Data Augmentation Method for Noise Robust Speaker Verification

Autor:	Kim, Wonbin, Shin, Hyun-seo, Kim, Ju-ho, Heo, Jungwoo, Lim, Chan-yeong, Yu, Ha-Jin
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Audio and Speech Processing Computer Science - Sound
Druh dokumentu:	Working Paper
Popis:	Background noise reduces speech intelligibility and quality, making speaker verification (SV) in noisy environments a challenging task. To improve the noise robustness of SV systems, additive noise data augmentation method has been commonly used. In this paper, we propose a new additive noise method, partial additive speech (PAS), which aims to train SV systems to be less affected by noisy environments. The experimental results demonstrate that PAS outperforms traditional additive noise in terms of equal error rates (EER), with relative improvements of 4.64% and 5.01% observed in SE-ResNet34 and ECAPA-TDNN. We also show the effectiveness of proposed method by analyzing attention modules and visualizing speaker embeddings. Comment: 5 pages, 2 figures, 1 table, accepted to CKAIA2023 as a conference paper
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2307.10628 Zobrazit plný text záznamu View this record from Arxiv