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S2S-Arena: Evaluating Paralinguistic Instruction Following in Speech-to-Speech Models
Feng Jiang, Zhiyu Lin, Yiyang Liu +6
Recent advances in large language models (LLMs) have fundamentally reshaped speech-to-speech (S2S) systems, enabling increasingly natural spoken interaction. However, existing benc…
EchoMind: An Interrelated Multi-level Benchmark for Evaluating Empathetic Speech Language Models
Li Zhou, Lutong Yu, You Lyu +6
Speech Language Models (SLMs) have made significant progress in spoken language understanding. Yet it remains unclear whether they can fully perceive non lexical vocal cues alongsi…
From Word to World: Evaluate and Mitigate Culture Bias in LLMs via Word Association Test
Xunlian Dai, Li Zhou, Benyou Wang +1
The human-centered word association test (WAT) serves as a cognitive proxy, revealing sociocultural variations through culturally shared semantic expectations and implicit linguist…
MTalk-Bench: Evaluating Speech-to-Speech Models in Multi-Turn Dialogues via Arena-style and Rubrics Protocols
Yuhao Du, Qianwei Huang, Guo Zhu +9
The rapid advancement of speech-to-speech (S2S) large language models (LLMs) has significantly improved real-time spoken interaction. However, current evaluation frameworks remain…
EchoX: Towards Mitigating Acoustic-Semantic Gap via Echo Training for Speech-to-Speech LLMs
Yuhao Zhang, Yuhao Du, Zhanchen Dai +4
Speech-to-speech large language models (SLLMs) are attracting increasing attention. Derived from text-based large language models (LLMs), SLLMs often exhibit degradation in knowled…
Leveraging Unit Language Guidance to Advance Speech Modeling in Textless Speech-to-Speech Translation
Yuhao Zhang, Xiangnan Ma, Kaiqi Kou +7
The success of building textless speech-to-speech translation (S2ST) models has attracted much attention. However, S2ST still faces two main challenges: 1) extracting linguistic fe…