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 …

Automatic methods to predict listener opinions of synthesized speech remain elusive since
listeners, systems being evaluated, characteristics of the speech, and even the instructions …

This study proposes a cross-domain multi-objective speech assessment model, called
MOSA-Net, which can simultaneously estimate the speech quality, intelligibility, and …

Personalizing a speech synthesis system is a highly desired application, where the system
can generate speech with the user's voice with rare enrolled recordings. There are two main …

An effective approach to automatically predict the subjective rating for synthetic speech is to
train on a listening test dataset with human-annotated scores. Although each speech sample …

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

Much of text-to-speech research relies on human evaluation. This incurs heavy costs and
slows down the development process, especially in heavily multilingual applications where …

Recent studies have shown how self-supervised models can produce accurate speech
quality predictions. Speech representations generated by the pre-trained wav2vec 2.0 …

Meetings are a pervasive method of communication within all types of companies and
organizations, and using remote collaboration systems to conduct meetings has increased …

Mean opinion score (MOS) is a typical subjective evaluation metric for speech synthesis
systems. Since collecting MOS is time-consuming, it would be desirable if there are accurate …