The VoiceMOS Challenge 2023: Zero-shot Subjective Speech Quality Prediction for Multiple Domains
We present the second edition of the VoiceMOS Challenge, a scientific event that aims to promote the study of automatic prediction of the mean opinion score (MOS) of synthesized and processed speech. This year, we emphasize real-world and challenging zero-shot out-of-domain MOS prediction with three tracks for three different voice evaluation scenarios. Ten teams from industry and academia in seven different countries participated. Surprisingly, we found that the two sub-tracks of French text-to-speech synthesis had large differences in their predictability, and that singing voice-converted samples were not as difficult to predict as we had expected. Use of diverse datasets and listener information during training appeared to be successful approaches.
Code (0)
등록된 구현이 없습니다.
Tasks
Speech Synthesistext-to-speechText to SpeechText-To-Speech SynthesisSimilar Papers 제목 키워드 기반
DDOS: A MOS Prediction Framework utilizing Domain Adaptive Pre-training and Distribution of Opinion Scores
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 MOS prediction models for automatic eva…
Self-Supervised LearningSpeech SynthesisUsing Rater and System Metadata to Explain Variance in the VoiceMOS Challenge 2022 Dataset
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…
text-to-speechText to SpeechVoice ConversionThe ZevoMOS entry to VoiceMOS Challenge 2022
This paper introduces the ZevoMOS entry to the main track of the VoiceMOS Challenge 2022. The ZevoMOS submission is based on a two-step finetuning of pretrained self-supervised learning (SSL) speech models. The first ste…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Self-Supervised Learningspeech-recognition+1Quality Assessment of Noisy and Enhanced Speech with Limited Data: UWB-NTIS System for VoiceMOS 2024 and Beyond
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 IT…
PredictionA Study on Incorporating Whisper for Robust Speech Assessment
This research introduces an enhanced version of the multi-objective speech assessment model--MOSA-Net+, by leveraging the acoustic features from Whisper, a large-scaled weakly supervised model. We first investigate the e…
Self-Supervised Learning