3 papers
eess.AS2026
Towards Fine-Grained Multi-Dimensional Speech Understanding: Data Pipeline, Benchmark, and Model
Guojian Li, Zhixian Zhao, Zhennan Lin +9
While speech Large Language Models (LLMs) excel at conventional tasks like basic speech recognition, they lack fine-grained, multi-dimensional perception. This deficiency is eviden…
eess.AS2026
Speaker-Reasoner: Scaling Interaction Turns and Reasoning Patterns for Timestamped Speaker-Attributed ASR
Zhennan Lin, Shuai Wang, Zhaokai Sun +5
Transcribing and understanding multi-speaker conversations requires speech recognition, speaker attribution, and timestamp localization. While speech LLMs excel at single-speaker t…
eess.AS2026
OmniCodec: Low Frame Rate Universal Audio Codec with Semantic-Acoustic Disentanglement
Jingbin Hu, Haoyu Zhang, Dake Guo +10
Large Language Models (LLMs) have advanced audio generation through discrete representation learning. However, most existing neural codecs focus on speech and emphasize reconstruct…