Improved Vocal Effort Transfer Vector Estimation for Vocal Effort-Robust Speaker Verification

Iván López-Espejo; Santi Prieto; Alfonso Ortega; Eduardo Lleida

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arXiv · 2305.02147

Improved Vocal Effort Transfer Vector Estimation for Vocal Effort-Robust Speaker Verification

Iván López-Espejo·Santi Prieto·Alfonso Ortega·Eduardo Lleida

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Abstract

Despite the maturity of modern speaker verification technology, its performance still significantly degrades when facing non-neutrally-phonated (e.g., shouted and whispered) speech. To address this issue, in this paper, we propose a new speaker embedding compensation method based on a minimum mean square error (MMSE) estimator. This method models the joint distribution of the vocal effort transfer vector and non-neutrally-phonated embedding spaces and operates in a principal component analysis domain to cope with non-neutrally-phonated speech data scarcity. Experiments are carried out using a cutting-edge speaker verification system integrating a powerful self-supervised pre-trained model for speech representation. In comparison with a state-of-the-art embedding compensation method, the proposed MMSE estimator yields superior and competitive equal error rate results when tackling shouted and whispered speech, respectively.

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Iván López-Espejo, Santi Prieto, Alfonso Ortega, Eduardo Lleida. 2023-05-03. Improved Vocal Effort Transfer Vector Estimation for Vocal Effort-Robust Speaker Verification. https://arxiv.org/abs/2305.02147

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