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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…
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…
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…
Unlocking Temporal Flexibility: Neural Speech Codec with Variable Frame Rate
Hanglei Zhang, Yiwei Guo, Zhihan Li +3
Most neural speech codecs achieve bitrate adjustment through intra-frame mechanisms, such as codebook dropout, at a Constant Frame Rate (CFR). However, speech segments inherently h…
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…
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…