Recent advances in speech generation are shifting toward context-aware, multi-turn, and multi-speaker synthesis. While these capabilities are in high demand for applications such as audiobook and audio drama production, evaluation has not kept pace with these advances. Beyond traditional zero-shot Text-to-Speech (TTS),...
Jing-Bin Hu, Zi-Tao Yang, Xiao-Ge Peng et al.· 0 citations
Dynamic speaking style adaptation in multi-turn multimodal interaction remains a major challenge for text-to-speech (TTS) systems. Existing context-aware TTS (CTTS) methods typically map dialogue context to speech in an end-to-end manner. Such implicit modeling makes contextual style decisions difficult to supervise, w...
Wen-Jie Tian, Kang-Xiang Xia, Jing-Bin Hu et al.· 0 citations
A controllable multi-speaker dialogue TTS framework that formulates synthesis as critique-driven iterative refinement, and unifies instruction-following synthesis and natural-language-guided attribute editing, enabling correction of expressive errors without full regeneration.
Kang-Xiang Xia, Xin-Fa Zhu, Hang-Rui Hu et al.· 0 citations
A Context-Aware Direct Preference Optimization (CA-DPO) method that significantly outperforms the baseline across all objective and subjective metrics, and establishes an evaluation method featuring a 500-sample test set and an LLM-as-Judge framework to independently assess reasoning and execution fidelity.
Jing-Bin Hu, Lu-Yu Wang, Wen-Jie Tian et al.· 0 citations
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