From the 1 of 36 linked papers with an AI index.
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Cross-modal Consistency Guidance for Robust Emotion Control in Auto-Regressive TTS Models
Yizhou Peng, Yukun Ma, Chong Zhang +4
While Text-to-Speech (TTS) systems enable emotional control via natural-language instructions, expressiveness, naturalness, and speech quality degrade when the target emotion confl…
Proactive for Uncertainty: Cause-Aware Error Diagnosis and Interactive Clarification for Spoken Dialogue Systems
Yizhou Peng, Ziyang Ma, Changsong Liu +3
Cascaded Automatic Speech Recognition -- Large Language Model (ASR-LLM) pipelines remain popular for industrial Spoken Dialogue Systems (SDS), primarily because their decoupled des…
Mind-Paced Speaking: A Dual-Brain Approach to Real-Time Reasoning in Spoken Language Models
Donghang Wu, Haoyang Zhang, Jun Chen +9
Real-time Spoken Language Models (SLMs) struggle to leverage Chain-of-Thought (CoT) reasoning due to the prohibitive latency of generating the entire thought process sequentially.…
CS-Sum: A Benchmark for Code-Switching Dialogue Summarization and the Limits of Large Language Models
Sathya Krishnan Suresh, Tanmay Surana, Lim Zhi Hao +1
Code-switching (CS) poses a significant challenge for Large Language Models (LLMs), yet its comprehensibility remains underexplored in LLMs. We introduce CS-Sum, to evaluate the co…
DiaSynth: Synthetic Dialogue Generation Framework for Low Resource Dialogue Applications
Sathya Krishnan Suresh, Wu Mengjun, Tushar Pranav +1
The scarcity of domain-specific dialogue datasets limits the development of dialogue systems across applications. Existing research is constrained by general or niche datasets that…
Large Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition
Chao-Han Huck Yang, Taejin Park, Yuan Gong +18
Given recent advances in generative AI technology, a key question is how large language models (LLMs) can enhance acoustic modeling tasks using text decoding results from a frozen,…