collaborators

6 papers

eess.AS2026

SpeakerCard-1M: An Evidence-Grounded Corpus for In-the-Wild Speaker Verification

Junyi Peng, Oldřich Plchot, Xiao Song +9

Modern speaker verification (SV) systems rely on speaker embeddings that are effective but difficult to interpret or query in natural language. Most existing speech-text corpora ta…

eess.AS2026

Reducing Linguistic Hallucination in LM-Based Speech Enhancement via Noise-Invariant Acoustic-Semantic Distillation

Zheng Wang, Xiaobin Rong, Hang Su +6

Language model (LM)-based speech enhancement (SE) can generate natural-sounding speech, but under severe noise it often suffers from unreliable conditioning, leading to perceptuall…

eess.AS2026

Listening with Time: Precise Temporal Awareness for Long-Form Audio Understanding

Mingchen Shao, Hang Su, Wenjie Tian +6

While Large Audio Language Models (LALMs) achieve strong performance on short audio, they degrade on long-form inputs. This degradation is more severe in temporal awareness tasks,…

cs.SD2026

Borderless Long Speech Synthesis

Xingchen Song, Di Wu, Dinghao Zhou +12

Most existing text-to-speech (TTS) systems either synthesize speech sentence by sentence and stitch the results together, or drive synthesis from plain-text dialogues alone. Both a…

cs.SD2026

Thinking in cocktail party: Chain-of-Thought and reinforcement learning for target speaker automatic speech recognition

Yiru Zhang, Hang Su, Lichun Fan +2

Target Speaker Automatic Speech Recognition (TS-ASR) aims to transcribe the speech of a specified target speaker from multi-speaker mixtures in cocktail party scenarios. Recent adv…

cs.SD2025

Omni-CLST: Error-aware Curriculum Learning with guided Selective chain-of-Thought for audio question answering

Jinghua Zhao, Hang Su, Lichun Fan +4

With the rapid progress of large audio-language models (LALMs), audio question answering (AQA) has emerged as a challenging task requiring both fine-grained audio understanding and…