collaborators

8 papers

eess.AS2025

BSCodec: A Band-Split Neural Codec for High-Quality Universal Audio Reconstruction

Haoran Wang, Jiatong Shi, Jinchuan Tian +3

Neural audio codecs have recently enabled high-fidelity reconstruction at high compression rates, especially for speech. However, speech and non-speech audio exhibit fundamentally…

cs.SD2025

ISA-Bench: Benchmarking Instruction Sensitivity for Large Audio Language Models

Bohan Li, Wenbin Huang, Yuhang Qiu +7

Large Audio Language Models (LALMs), which couple acoustic perception with large language models (LLMs) to extract and understand diverse information from audio, have attracted int…

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…

cs.SD2025

Robust and Efficient Autoregressive Speech Synthesis with Dynamic Chunk-wise Prediction Policy

Bohan Li, Zhihan Li, Haoran Wang +5

Recently, autoregressive (AR) language models have emerged as a dominant approach in speech synthesis, offering expressive generation and scalable training. However, conventional A…

eess.AS2025

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…

cs.SD2025

Towards General Discrete Speech Codec for Complex Acoustic Environments: A Study of Reconstruction and Downstream Task Consistency

Haoran Wang, Guanyu Chen, Bohan Li +5

Neural speech codecs excel in reconstructing clean speech signals; however, their efficacy in complex acoustic environments and downstream signal processing tasks remains underexpl…