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20242026
most citedListen and Speak Fairly: A Study on Semantic Gender Bias in Speech Integrated Large Language Models

7 citations · 14 across the 14 of their papers we have counts for

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cs.CL2024

Building a Taiwanese Mandarin Spoken Language Model: A First Attempt

Chih-Kai Yang, Yu-Kuan Fu, Chen-An Li +18

This technical report presents our initial attempt to build a spoken large language model (LLM) for Taiwanese Mandarin, specifically tailored to enable real-time, speech-to-speech…

cs.CL2024

Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks

Chien-yu Huang, Wei-Chih Chen, Shu-wen Yang +77

Multimodal foundation models, such as Gemini and ChatGPT, have revolutionized human-machine interactions by seamlessly integrating various forms of data. Developing a universal spo…

cs.CL2024★ 5 cited

Spoken Stereoset: On Evaluating Social Bias Toward Speaker in Speech Large Language Models

Yi-Cheng Lin, Wei-Chih Chen, Hung-yi Lee

Warning: This paper may contain texts with uncomfortable content. Large Language Models (LLMs) have achieved remarkable performance in various tasks, including those involving mult…

eess.AS2024★ 7 cited

Listen and Speak Fairly: A Study on Semantic Gender Bias in Speech Integrated Large Language Models

Yi-Cheng Lin, Tzu-Quan Lin, Chih-Kai Yang +4

Speech Integrated Large Language Models (SILLMs) combine large language models with speech perception to perform diverse tasks, such as emotion recognition to speaker verification,…

cs.CL2024★ 1 cited

Large Language Model as an Assignment Evaluator: Insights, Feedback, and Challenges in a 1000+ Student Course

Cheng-Han Chiang, Wei-Chih Chen, Chun-Yi Kuan +2

Using large language models (LLMs) for automatic evaluation has become an important evaluation method in NLP research. However, it is unclear whether these LLM-based evaluators can…