Web: http://arxiv.org/abs/2209.06358

Sept. 15, 2022, 1:11 a.m. | Michael Chinen, Jan Skoglund, Chandan K A Reddy, Alessandro Ragano, Andrew Hines

cs.LG updates on arXiv.org arxiv.org

Non-reference speech quality models are important for a growing number of
applications. The VoiceMOS 2022 challenge provided a dataset of synthetic voice
conversion and text-to-speech samples with subjective labels. This study looks
at the amount of variance that can be explained in subjective ratings of speech
quality from metadata and the distribution imbalances of the dataset. Speech
quality models were constructed using wav2vec 2.0 with additional metadata
features that included rater groups and system identifiers and obtained
competitive metrics including …

arxiv challenge dataset metadata variance

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