Quality Assessment of Noisy and Enhanced Speech with Limited Data: UWB-NTIS System for VoiceMOS 2024 and Beyond

Abstract: In this preprint, we present the UWB-NTIS-TTS team's submission to Track 3 of the VoiceMOS 2024 Challenge, the goal of which was to automatically assess the speech quality of noisy and de-noised speech in terms of the ITU-T P.835 metrics of "SIG", "BAK", and "OVRL". Our proposed system, based on wav2vec 2.0, placed among the top systems in the challenge, achieving the best prediction of the BAK scores (background noise intrusiveness), the second-best prediction of the OVRL score (overall audio quality), and the third-best prediction of SIG (speech signal quality) out of the five participating systems. We describe our approach, such as the two-stage fine-tuning process we used to contend with the challenge's very limiting restrictions on allowable training data, and present the results achieved both on the VoiceMOS 2024 Challenge data and on the recently released CHiME 7 - UDASE dataset.