3 papers
eess.AS2026
Enhancing Conversational TTS with Cascaded Prompting and ICL-Based Online Reinforcement Learning
Zhicheng Ouyang, Seong-Gyun Leem, Bach Viet Do +4
Conversational AI has made significant progress, yet generating expressive and controllable text-to-speech (TTS) remains challenging. Specifically, controlling fine-grained voice s…
cs.CL2026
Aligning Paralinguistic Understanding and Generation in Speech LLMs via Multi-Task Reinforcement Learning
Jingxiang Chen, Minseok Kim, Seong-Gyun Leem +13
Speech large language models (LLMs) observe paralinguistic cues such as prosody, emotion, and non-verbal sounds--crucial for intent understanding. However, leveraging these cues fa…
eess.AS2026
Conversational Speech Naturalness Predictor
Anfeng Xu, Yashesh Gaur, Naoyuki Kanda +6
Evaluation of conversational naturalness is essential for developing human-like speech agents. However, existing speech naturalness predictors are often designed to assess utteranc…