We present the first edition of the VoiceMOS Challenge, a scientific event that aims to
promote the study of automatic prediction of the mean opinion score (MOS) of synthetic …

Mean opinion score (MOS) is a popular subjective metric to assess the quality of
synthesized speech, and usually involves multiple human judges to evaluate each speech …

The Voice Conversion Challenge 2020 is the third edition under its flagship that promotes
intra-lingual semiparallel and cross-lingual voice conversion (VC). While the primary …

Evaluating synthetic speech generated by machines is a complicated process, as it involves
judging along multiple dimensions including naturalness, intelligibility, and whether the …

In this work, we present the SOMOS dataset, the first large-scale mean opinion scores
(MOS) dataset consisting of solely neural text-to-speech (TTS) samples. It can be employed …

Several studies have proposed deep-learning-based models to predict the mean opinion
score (MOS) of synthesized speech, showing the possibility of replacing human raters …

We propose a deep neural network (DNN) based method that provides a posterior
distribution of mean-opinion-score (MOS) for an input speech signal. The DNN outputs …

Traditionally, speech quality evaluation relies on subjective assessments or intrusive
methods that require reference signals or additional equipment. However, over recent years …

Automatic speech recognition (ASR) is increasingly used to evaluate the intelligibility of text-
to-speech synthesis (TTS). ASR is less costly than traditional listening tests, but questions …

This paper presents the details of the BIT-MI deep learningbased model submitted to the
ConferencingSpeech challenge 2022. Due to the large time and labor costs of subjective …