WordVoice

WordVoice: Word-level acoustic control framework for LLM-based TTS with 4.7k-hour bilingual dataset

Researchers propose WordVoice, a framework enabling explicit, decoupled word-level control over acoustic attributes (duration, boundary, energy, pitch, tone) in LLM-based text-to-speech systems. The work introduces a bound-token mechanism for acoustic planning within the LLM and a fine-grained modulation module to align discrete tokens with continuous waveforms. Accompanying the model is WordVoice-5A, a 4.7k-hour bilingual annotated dataset with five-dimensional word-level labels. The system targets high-precision applications such as audiobook narration and video dubbing where implicit TTS generation falls short.