Automatic Voice Identification after Speech Resynthesis using PPG

Fuente: arXiv
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Autori principali: Gaudier, Thibault, Tahon, Marie, Larcher, Anthony, Estève, Yannick
Natura: Preprint
Pubblicazione: 2024
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author Gaudier, Thibault
Tahon, Marie
Larcher, Anthony
Estève, Yannick
author_facet Gaudier, Thibault
Tahon, Marie
Larcher, Anthony
Estève, Yannick
contents Speech resynthesis is a generic task for which we want to synthesize audio with another audio as input, which finds applications for media monitors and journalists.Among different tasks addressed by speech resynthesis, voice conversion preserves the linguistic information while modifying the identity of the speaker, and speech edition preserves the identity of the speaker but some words are modified.In both cases, we need to disentangle speaker and phonetic contents in intermediate representations.Phonetic PosteriorGrams (PPG) are a frame-level probabilistic representation of phonemes, and are usually considered speaker-independent.This paper presents a PPG-based speech resynthesis system.A perceptive evaluation assesses that it produces correct audio quality.Then, we demonstrate that an automatic speaker verification model is not able to recover the source speaker after re-synthesis with PPG, even when the model is trained on synthetic data.
format Preprint
id arxiv_https___arxiv_org_abs_2408_02712
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Automatic Voice Identification after Speech Resynthesis using PPG
Gaudier, Thibault
Tahon, Marie
Larcher, Anthony
Estève, Yannick
Sound
Artificial Intelligence
Neural and Evolutionary Computing
Audio and Speech Processing
Signal Processing
Speech resynthesis is a generic task for which we want to synthesize audio with another audio as input, which finds applications for media monitors and journalists.Among different tasks addressed by speech resynthesis, voice conversion preserves the linguistic information while modifying the identity of the speaker, and speech edition preserves the identity of the speaker but some words are modified.In both cases, we need to disentangle speaker and phonetic contents in intermediate representations.Phonetic PosteriorGrams (PPG) are a frame-level probabilistic representation of phonemes, and are usually considered speaker-independent.This paper presents a PPG-based speech resynthesis system.A perceptive evaluation assesses that it produces correct audio quality.Then, we demonstrate that an automatic speaker verification model is not able to recover the source speaker after re-synthesis with PPG, even when the model is trained on synthetic data.
title Automatic Voice Identification after Speech Resynthesis using PPG
topic Sound
Artificial Intelligence
Neural and Evolutionary Computing
Audio and Speech Processing
Signal Processing
url https://arxiv.org/abs/2408.02712