6 papers
Style Amnesia: Investigating Speaking Style Degradation and Mitigation in Multi-Turn Spoken Language Models
Yu-Xiang Lin, Cheng-Han Chiang, Hung-yi Lee
In this paper, we show that when spoken language models (SLMs) are instructed to speak in a specific speaking style at the beginning of a multi-turn conversation, they cannot maint…
SHANKS: Simultaneous Hearing and Thinking for Spoken Language Models
Cheng-Han Chiang, Xiaofei Wang, Linjie Li +7
Current large language models (LLMs) and spoken language models (SLMs) begin thinking and taking actions only after the user has finished their turn. This prevents the model from i…
STITCH: Simultaneous Thinking and Talking with Chunked Reasoning for Spoken Language Models
Cheng-Han Chiang, Xiaofei Wang, Linjie Li +7
Spoken Language Models (SLMs) are designed to take speech inputs and produce spoken responses. However, current SLMs lack the ability to perform an internal, unspoken thinking proc…
Audio-Aware Large Language Models as Judges for Speaking Styles
Cheng-Han Chiang, Xiaofei Wang, Chung-Ching Lin +8
Audio-aware large language models (ALLMs) can understand the textual and non-textual information in the audio input. In this paper, we explore using ALLMs as an automatic judge to…
Reducing Object Hallucination in Large Audio-Language Models via Audio-Aware Decoding
Tzu-wen Hsu, Ke-Han Lu, Cheng-Han Chiang +1
Large Audio-Language Models (LALMs) can take audio and text as the inputs and answer questions about the audio. While prior LALMs have shown strong performance on standard benchmar…
TRACT: Regression-Aware Fine-tuning Meets Chain-of-Thought Reasoning for LLM-as-a-Judge
Cheng-Han Chiang, Hung-yi Lee, Michal Lukasik
The LLM-as-a-judge paradigm uses large language models (LLMs) for automated text evaluation, where a numerical assessment is assigned by an LLM to the input text following scoring…