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20242026
most citedEnhancing Multimodal Emotion Recognition through Multi-Granularity Cross-Modal Alignment

1 citations · 1 across the 10 of their papers we have counts for

collaborators

17 papers

cs.SD2026

Speech-XL: Towards Long-Form Speech Understanding in Large Speech Language Models

Haoqin Sun, Chenyang Lyu, Shiwan Zhao +5

Despite the growing success of Large Speech Language Models (LSLMs) in processing short-term acoustic signals, their extension to long-form audio understanding is severely bottlene…

cs.SD2026

DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding

Jiaming Zhou, Xuxin Cheng, Shiwan Zhao +5

Autoregressive (AR) large audio language models (LALMs) such as Qwen-2.5-Omni have achieved strong performance on audio understanding and interaction, but scaling them remains cost…

cs.SD2025

Zero- and One-Shot Data Augmentation for Sentence-Level Dysarthric Speech Recognition in Constrained Scenarios

Shiyao Wang, Shiwan Zhao, Jiaming Zhou +1

Dysarthric speech recognition (DSR) research has witnessed remarkable progress in recent years, evolving from the basic understanding of individual words to the intricate comprehen…

cs.SD2025

MECap-R1: Emotion-aware Policy with Reinforcement Learning for Multimodal Emotion Captioning

Haoqin Sun, Chenyang Lyu, Xiangyu Kong +9

Speech Emotion Captioning (SEC) has emerged as a notable research direction. The inherent complexity of emotional content in human speech makes it challenging for traditional discr…

cs.SD2025

TTA-Bench: A Comprehensive Benchmark for Evaluating Text-to-Audio Models

Hui Wang, Cheng Liu, Junyang Chen +7

Text-to-Audio (TTA) generation has made rapid progress, but current evaluation methods remain narrow, focusing mainly on perceptual quality while overlooking robustness, generaliza…

cs.CL2025

RealTalk-CN: A Realistic Chinese Speech-Text Dialogue Benchmark With Cross-Modal Interaction Analysis

Enzhi Wang, Qicheng Li, Shiwan Zhao +6

In recent years, large language models (LLMs) have achieved remarkable advancements in multimodal processing, including end-to-end speech-based language models that enable natural…