VoxSim: A perceptual voice similarity dataset

Fuente: arXiv
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Main Authors: Ahn, Junseok, Kim, Youkyum, Choi, Yeunju, Kwak, Doyeop, Kim, Ji-Hoon, Mun, Seongkyu, Chung, Joon Son
Format: Preprint
Published: 2024
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author Ahn, Junseok
Kim, Youkyum
Choi, Yeunju
Kwak, Doyeop
Kim, Ji-Hoon
Mun, Seongkyu
Chung, Joon Son
author_facet Ahn, Junseok
Kim, Youkyum
Choi, Yeunju
Kwak, Doyeop
Kim, Ji-Hoon
Mun, Seongkyu
Chung, Joon Son
contents This paper introduces VoxSim, a dataset of perceptual voice similarity ratings. Recent efforts to automate the assessment of speech synthesis technologies have primarily focused on predicting mean opinion score of naturalness, leaving speaker voice similarity relatively unexplored due to a lack of extensive training data. To address this, we generate about 41k utterance pairs from the VoxCeleb dataset, a widely utilised speech dataset for speaker recognition, and collect nearly 70k speaker similarity scores through a listening test. VoxSim offers a valuable resource for the development and benchmarking of speaker similarity prediction models. We provide baseline results of speaker similarity prediction models on the VoxSim test set and further demonstrate that the model trained on our dataset generalises to the out-of-domain VCC2018 dataset.
format Preprint
id arxiv_https___arxiv_org_abs_2407_18505
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle VoxSim: A perceptual voice similarity dataset
Ahn, Junseok
Kim, Youkyum
Choi, Yeunju
Kwak, Doyeop
Kim, Ji-Hoon
Mun, Seongkyu
Chung, Joon Son
Audio and Speech Processing
This paper introduces VoxSim, a dataset of perceptual voice similarity ratings. Recent efforts to automate the assessment of speech synthesis technologies have primarily focused on predicting mean opinion score of naturalness, leaving speaker voice similarity relatively unexplored due to a lack of extensive training data. To address this, we generate about 41k utterance pairs from the VoxCeleb dataset, a widely utilised speech dataset for speaker recognition, and collect nearly 70k speaker similarity scores through a listening test. VoxSim offers a valuable resource for the development and benchmarking of speaker similarity prediction models. We provide baseline results of speaker similarity prediction models on the VoxSim test set and further demonstrate that the model trained on our dataset generalises to the out-of-domain VCC2018 dataset.
title VoxSim: A perceptual voice similarity dataset
topic Audio and Speech Processing
url https://arxiv.org/abs/2407.18505