Predicting pairwise preferences between TTS audio stimuli using parallel ratings data and anti-symmetric twin neural networks. (arXiv:2209.11003v1 [cs.SD])

Automatically predicting the outcome of subjective listening tests is a
challenging task. Ratings may vary from person to person even if preferences
are consistent across listeners. While previous work has focused on predicting
listeners' ratings (mean opinion scores) of individual stimuli, we focus on the
simpler task of predicting subjective preference given two speech stimuli for
the same text. We propose a model based on anti-symmetric twin neural networks,
trained on pairs of waveforms and their corresponding preference scores. We …

arxiv audio data networks neural networks tts