Adaptive Duration Model for Text Speech Alignment
The DurFormer framework is a novel duration prediction model designed for speech-to-text alignment in neural TTS. It predicts phoneme-level durations using text input, speech speed, and scene conditions. This approach offers more precise alignment and better adaptation to different conditions than previous methods, improving zero-shot TTS robustness.