Combining wav2vec2 semantic features, BiVocoder acoustic features, and listener IDs in a multi-task MOS predictor improves system-level naturalness ranking on BVCC while remaining competitive on out-of-domain BC2019.
When the rater ID is not the mean-listener, the label representing the sample is the score given by the individual rater (an integer i from 1 to 5)
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SAMOS: A Neural MOS Prediction Model Leveraging Semantic Representations and Acoustic Features
Combining wav2vec2 semantic features, BiVocoder acoustic features, and listener IDs in a multi-task MOS predictor improves system-level naturalness ranking on BVCC while remaining competitive on out-of-domain BC2019.