Jiutian Artificial Intelligence Research Institute
This research introduces Group Relative Policy Optimization (GRPO) with a novel off-the-shelf ASR-derived composite reward to fine-tune large language model (LLM)-based Text-to-Speech (TTS) models. The approach enhances speech intelligibility and naturalness, achieving consistent improvements in character/word error rates and Mean Opinion Scores across multiple languages and diverse LLM-TTS architectures.
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