1 citations · 1 across the 13 of their papers we have counts for
16 papers
SURE-EVAL: A Systematic and Unified Agentic Framework for Reproducible Evaluation
Jing Peng, Junhao Du, Yixuan Wang +21
Audio and speech models are released rapidly, but reported scores often conflate model capability with deployment and evaluation choices. The same checkpoint can produce different…
WenetSpeech-Min: A Large-Scale Minnan Speech Corpus with Dual Transcriptions for Dialectal Speech Processing
Haoyu Zhang, Chunjiang He, Hongtao Li +17
Progress in dialectal speech technology is hindered by the scarcity of large-scale, real-world corpora. For Minnan speech, existing resources remain limited, and few provide paired…
The SLT 2026 SmartGlasses Challenge: Benchmarking Egocentric Multi-Talker Speech Recognition and Understanding with Audio-Language Models
Dehui Gao, Zhixian Zhao, Zhennan Lin +14
Recent advances in large language models (LLMs) and multimodal LLMs (MLLMs) have created new opportunities for wearable speech interfaces, with smart glasses providing an egocentri…
Harness TTS: Towards Context-Aware Expressive Speech Synthesis with Harness Layer
Shengfan Shen, Di Wu, Xingchen Song +5
Expressive speech synthesis for voice assistants requires flexible style control that adapts to explicit requests and broader interaction context. We propose Harness TTS, a lightwe…
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…
MSU-Bench: Towards Speaker-Centric Understanding in Conversational Multi-Speaker Scenarios
Zhaokai Sun, Shuai Wang, Zhennan Lin +6
Spoken Language Understanding (SLU) is moving from task-specific pipelines toward large audio language models (LALMs) that generate natural-language responses. However, existing sp…
Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning
Yixian Shen, Zhiheng Yang, Qi Bi +6
Multimodal spatial reasoning often relies on long chains of intermediate textual and visual thoughts, where accumulating visual tokens and dense cross-modal attention incur substan…
A Unified and Reproducible Experimentation Framework for Speech Understanding
Jing Peng, Junhao Du, Chenghao Wang +21
Speech foundation models and Speech LLMs have advanced speech understanding, yet deployment-oriented model selection is hindered by non-comparable evaluations caused by mismatched…
Audio-Mind: An Auditable Agentic Framework for Audio Understanding
Yucheng Wang, Jing Peng, Hanqi Li +6
Audio agents extend large audio-language models (LALMs) by decomposing audio questions into tool calls, intermediate evidence, and iterative reasoning steps. However, as LALMs beco…
Representation Forcing for Bottleneck-Free Unified Multimodal Models
Yuqing Wang, Zhijie Lin, Ceyuan Yang +10
Unified multimodal models (UMMs) aim to handle perception and generation in a single model. Yet existing UMMs still rely on a frozen, separately pretrained VAE for image generation…
Full-Duplex Interaction in Spoken Dialogue Systems: A Comprehensive Study from the ICASSP 2026 HumDial Challenge
Chengyou Wang, Hongfei Xue, Guojian Li +6
Full-duplex interaction, where speakers and listeners converse simultaneously, is a key element of human communication often missing from traditional spoken dialogue systems. These…
HumDial-EIBench: A Human-Recorded Multi-Turn Emotional Intelligence Benchmark for Audio Language Models
Shuiyuan Wang, Zhixian Zhao, Hongfei Xue +5
Evaluating the emotional intelligence (EI) of audio language models (ALMs) is critical. However, existing benchmarks mostly rely on synthesized speech, are limited to single-turn i…
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…
The ICASSP 2026 HumDial Challenge: Benchmarking Human-like Spoken Dialogue Systems in the LLM Era
Zhixian Zhao, Shuiyuan Wang, Guojian Li +12
Driven by the rapid advancement of Large Language Models (LLMs), particularly Audio-LLMs and Omni-models, spoken dialogue systems have evolved significantly, progressively narrowin…
Summary on The Multilingual Conversational Speech Language Model Challenge: Datasets, Tasks, Baselines, and Methods
Bingshen Mu, Pengcheng Guo, Zhaokai Sun +8
This paper summarizes the Interspeech2025 Multilingual Conversational Speech Language Model (MLC-SLM) challenge, which aims to advance the exploration of building effective multili…
MSU-Bench: Towards Understanding the Conversational Multi-talker Scenarios
Shuai Wang, Zhaokai Sun, Zhennan Lin +3
Spoken Language Understanding (SLU) has progressed from traditional single-task methods to large audio language model (LALM) solutions. Yet, most existing speech benchmarks focus o…