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eess.AS2026

Read What You Hear: Reference-Free Hypotheses Evaluation with Acoustic Discrepancy

Zhihan Li, Hankun Wang, Yiwei Guo +3

Automatic speech recognition systems commonly rely on reference transcriptions for evaluation, while reference-free approaches often depend on internal confidence estimation or aux…

eess.AS2026

Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios

Changhao Pan, Rui Yang, Han Wang +12

Recent advances in speech generation have enabled high-fidelity synthesis, yet systematic evaluation of models under long-context conditions remains largely underexplored. A compre…

eess.AS2026

CodecSlime: Temporal Redundancy Compression of Neural Speech Codec via Dynamic Frame Rate

Hankun Wang, Yiwei Guo, Chongtian Shao +2

Neural speech codecs have been widely used in audio compression and various downstream tasks. Current mainstream codecs are fixed-frame-rate (FFR), which allocate the same number o…

eess.AS2026

Why Do Speech Language Models Fail to Generate Semantically Coherent Outputs? A Modality Evolving Perspective

Hankun Wang, Haoran Wang, Yiwei Guo +3

Although text-based large language models exhibit human-level writing ability and remarkable intelligence, speech language models (SLMs) still struggle to generate semantically coh…

eess.AS2025

Recent Advances in Discrete Speech Tokens: A Review

Yiwei Guo, Zhihan Li, Hankun Wang +7

The rapid advancement of speech generation technologies in the era of large language models (LLMs) has established discrete speech tokens as a foundational paradigm for speech repr…

eess.AS2025

AHAMask: Reliable Task Specification for Large Audio Language Models without Instructions

Yiwei Guo, Bohan Li, Hankun Wang +4

Although current large audio language models (LALMs) extend text large language models (LLMs) with generic acoustic understanding abilities, they usually suffer from prompt sensiti…