5 papers
Think Smart, Not Hard: Difficulty Adaptive Reasoning for Large Audio Language Models
Zhichao Sheng, Shilin Zhou, Chen Gong +1
Large Audio Language Models (LALMs), powered by the chain-of-thought (CoT) paradigm, have shown remarkable reasoning capabilities. Intuitively, different problems often require var…
UniSLU: Unified Spoken Language Understanding from Heterogeneous Cross-Task Datasets
Zhichao Sheng, Shilin Zhou, Chen Gong +1
Spoken Language Understanding (SLU) plays a crucial role in speech-centric multimedia applications, enabling machines to comprehend spoken language in scenarios such as meetings, i…
Improving Contextual ASR via Multi-grained Fusion with Large Language Models
Shilin Zhou, Zhenghua Li
While end-to-end Automatic Speech Recognition (ASR) models have shown impressive performance in transcribing general speech, they often struggle to accurately recognize contextuall…
Nexus: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision
Che Liu, Yingji Zhang, Dong Zhang +13
This work proposes an industry-level omni-modal large language model (LLM) pipeline that integrates auditory, visual, and linguistic modalities to overcome challenges such as limit…
Mining Word Boundaries from Speech-Text Parallel Data for Cross-domain Chinese Word Segmentation
Xuebin Wang, Lei Zhang, Zhenghua Li +3
Inspired by early research on exploring naturally annotated data for Chinese Word Segmentation (CWS), and also by recent research on integration of speech and text processing, this…