arXiv AI October 16, 2026 By Junjie Cao

Adaptive Duration Model for Text Speech Alignment

The paper introduces an Adaptive Duration Model designed to predict phoneme-level duration distributions directly from text, improving alignment in text-to-speech systems. It outperforms existing baseline models in precision and adaptability to varying conditions, enhancing phoneme-level alignment accuracy. The model also strengthens zero‑shot TTS performance by reducing sensitivity to mismatches between prompt and input audio.

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