Papers by Radu Kopetz
Audio-Aware Large Language Models as Judges for Speaking Styles (2025.findings-emnlp)
Copied to clipboard
Cheng-Han Chiang, Xiaofei Wang, Chung-Ching Lin, Kevin Lin, Linjie Li, Radu Kopetz, Yao Qian, Zhendong Wang, Zhengyuan Yang, Hung-yi Lee, Lijuan Wang
| Challenge: | Audio-aware large language models (ALLMs) can understand textual and non-textual information in the audio input. |
| Approach: | They use audio-aware large language models (ALLMs) to evaluate the speaking styles of SLMs on two tasks: voice style instruction following and role-playing. |
| Outcome: | The proposed models can understand the textual and non-textual information in the audio input and can be used as a judge to assess the speaking styles of SLMs. |