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Main Authors: Lechler, Laura, Wojcicki, Kamil
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.14817
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author Lechler, Laura
Wojcicki, Kamil
author_facet Lechler, Laura
Wojcicki, Kamil
contents With the advent of generative audio features, there is an increasing need for rapid evaluation of their impact on speech intelligibility. Beyond the existing laboratory measures, which are expensive and do not scale well, there has been comparatively little work on crowdsourced assessment of intelligibility. Standards and recommendations are yet to be defined, and publicly available multilingual test materials are lacking. In response to this challenge, we propose an approach for a crowdsourced intelligibility assessment. We detail the test design, the collection and public release of the multilingual speech data, and the results of our early experiments.
format Preprint
id arxiv_https___arxiv_org_abs_2403_14817
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Crowdsourced Multilingual Speech Intelligibility Testing
Lechler, Laura
Wojcicki, Kamil
Audio and Speech Processing
Artificial Intelligence
Signal Processing
With the advent of generative audio features, there is an increasing need for rapid evaluation of their impact on speech intelligibility. Beyond the existing laboratory measures, which are expensive and do not scale well, there has been comparatively little work on crowdsourced assessment of intelligibility. Standards and recommendations are yet to be defined, and publicly available multilingual test materials are lacking. In response to this challenge, we propose an approach for a crowdsourced intelligibility assessment. We detail the test design, the collection and public release of the multilingual speech data, and the results of our early experiments.
title Crowdsourced Multilingual Speech Intelligibility Testing
topic Audio and Speech Processing
Artificial Intelligence
Signal Processing
url https://arxiv.org/abs/2403.14817