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20242026
most citedA Survey on Speech Large Language Models for Understanding

6 citations · 6 across the 15 of their papers we have counts for

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8 papers · 1 filter

eess.AS2026

SURE-Tagger: Structured Speech Representations for Compositional Evaluation and Targeted Data Selection

Jing Peng, Huifei Wang, Weihan Chen +11

Speech conveys linguistic content, speaker characteristics, temporal interactions, paralinguistic cues, and acoustic environments. While recent speech captioning models describe th…

eess.AS2026

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…

eess.AS2026

Pruned CTC for Memory-Efficient Large-Vocabulary ASR Training

Yifan Yang, Xiaoyu Yang, Zengrui Jin +10

Connectionist temporal classification (CTC) naturally supports offline and streaming speech recognition with utterance-level supervision, but conventional implementations materiali…

eess.AS2026

DAMSEP: Distance-Aware Monaural Source Separation using Multi-RIR Estimation

Wen Wen, Qiang Zhou, Yu Xi +3

Although room impulse responses (RIRs) encode source-distance cues, conventional monaural source separation focuses on recovering audio content without estimating source-specific R…

eess.AS2026

DiaScriber: A Speech LLM for Joint Diarization and Transcription in Multi-Speaker Scenarios

Bingshen Mu, Xian Shi, Xiong Wang +6

Multi-speaker automatic speech recognition (MSASR) aims to jointly predict content transcriptions, speaker identities, and timestamps, thereby addressing the key question of "who s…

eess.AS2026

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…

cs.SD2026

HoliTok: A Continuous Holistic Tokenization with Robust Dual Capabilities of Speech Generation and Understanding

Bohan Li, Shi Lian, Hankun Wang +6

Unified speech foundation models require a holistic tokenization space that is both learnable by language models and decodable into high-quality waveforms. Existing speech tokenize…

eess.AS2026

Detect, Attend and Extract: Keyword Guided Target Speaker Extraction

Haoyu Li, Yu Xi, Yidi Jiang +5

Target speaker extraction (TSE) aims to extract the speech of a target speaker from mixtures containing multiple competing speakers. Conventional TSE systems predominantly rely on…