5 papers
Emo-LiPO: Listwise Preference Optimization for Fine-Grained Emotion Intensity Control in LLM-based Text-to-Speech
Yihang Lin, Li Zhou, Congwei Cao +4
Large language model (LLM)-based text-to-speech (TTS) systems enable prompt-conditioned emotional control but struggle with fine-grained emotion intensity due to the semantic -- ac…
PAL: Prompting Analytic Learning with Missing Modality for Multi-Modal Class-Incremental Learning
Xianghu Yue, Yiming Chen, Xueyi Zhang +5
Multi-modal class-incremental learning (MMCIL) seeks to leverage multi-modal data, such as audio-visual and image-text pairs, thereby enabling models to learn continuously across a…
VoiceBench: Benchmarking LLM-Based Voice Assistants
Yiming Chen, Xianghu Yue, Chen Zhang +3
Building on the success of large language models (LLMs), recent advancements such as GPT-4o have enabled real-time speech interactions through LLM-based voice assistants, offering…
Transferable Adversarial Attacks against ASR
Xiaoxue Gao, Zexin Li, Yiming Chen +2
Given the extensive research and real-world applications of automatic speech recognition (ASR), ensuring the robustness of ASR models against minor input perturbations becomes a cr…
Beyond Single-Audio: Advancing Multi-Audio Processing in Audio Large Language Models
Yiming Chen, Xianghu Yue, Xiaoxue Gao +4
Various audio-LLMs (ALLMs) have been explored recently for tackling different audio tasks simultaneously using a single, unified model. While existing evaluations of ALLMs primaril…