Neural networks for Text-to-Speech evaluation

This research introduces novel neural models to automate the evaluation of Text-to-Speech (TTS) system quality, addressing the limitations of traditional human subjective assessments. It proposes NeuralSBS for relative evaluations and enhancements to MOSNet and WhisperBert for absolute assessments, aiming to approximate expert judgments efficiently.