6 citations · 6 across the 21 of their papers we have counts for
24 papers
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…
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…
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…
dots.tts.edit: Precisely Controlled Speech Editing with a Continuous Autoregressive Model
Hankun Wang, Bohan Li, Shi Lian +7
Speech editing for content creation requires precise control over both what an edit should do and where it should apply. Free-form natural language provides a flexible interface fo…
SLT 2026 REAL-TSE Challenge: Real-world Target Speaker Extraction from Conversational Recordings
Shuai Wang, Zihan Qian, Ke Zhang +9
We introduce the REAL-TSE Challenge, an IEEE SLT 2026 satellite challenge on target speaker extraction~(TSE) from real conversational recordings. Given a multi-speaker mixture and…
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…
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…
Dual-LoRA: Parameter-Efficient Adversarial Disentanglement for Cross-Lingual Speaker Verification
Qituan Shangguan, Junhao Du, Kunyang Peng +5
Cross-lingual speaker verification suffers from severe language-speaker entanglement. This causes systematic degradation in the hardest scenario: correctly accepting utterances fro…
TASU2: Controllable CTC Simulation for Alignment and Low-Resource Adaptation of Speech LLMs
Jing Peng, Chenghao Wang, Yi Yang +5
Speech LLM post-training increasingly relies on efficient cross-modal alignment and robust low-resource adaptation, yet collecting large-scale audio-text pairs remains costly. Text…
G-STAR: End-to-End Global Speaker-Tracking Attributed Recognition
Jing Peng, Ziyi Chen, Haoyu Li +7
We study timestamped speaker-attributed automatic speech recognition (SA-ASR) for long-form, multi-party speech with overlap. In this setting, chunk-wise inference must preserve me…
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…
Time-Layer Adaptive Alignment for Speaker Similarity in Flow-Matching Based Zero-Shot TTS
Haoyu Li, Mingyang Han, Yu Xi +8
Flow-Matching (FM)-based zero-shot text-to-speech (TTS) systems exhibit high-quality speech synthesis and robust generalization capabilities. However, the speaker representation ab…
Joint decoding method for controllable contextual speech recognition based on Speech LLM
Yangui Fang, Jing Peng, Yu Xi +5
Contextual speech recognition refers to the ability to identify preferences for specific content based on contextual information. Recently, leveraging the contextual understanding…
MFA-KWS: Effective Keyword Spotting with Multi-head Frame-asynchronous Decoding
Yu Xi, Haoyu Li, Xiaoyu Gu +2
Keyword spotting (KWS) is essential for voice-driven applications, demanding both accuracy and efficiency. Traditional ASR-based KWS methods, such as greedy and beam search, explor…
Low-Resource Domain Adaptation for Speech LLMs via Text-Only Fine-Tuning
Yangui Fang, Jing Peng, Xu Li +4
Recent advances in automatic speech recognition (ASR) have combined speech encoders with large language models (LLMs) through projection, forming Speech LLMs with strong performanc…
Masked Self-distilled Transducer-based Keyword Spotting with Semi-autoregressive Decoding
Yu Xi, Xiaoyu Gu, Haoyu Li +3
RNN-T-based keyword spotting (KWS) with autoregressive decoding~(AR) has gained attention due to its streaming architecture and superior performance. However, the simplicity of the…
Neural Directed Speech Enhancement with Dual Microphone Array in High Noise Scenario
Wen Wen, Qiang Zhou, Yu Xi +3
In multi-speaker scenarios, leveraging spatial features is essential for enhancing target speech. While with limited microphone arrays, developing a compact multi-channel speech en…
Streaming Keyword Spotting Boosted by Cross-layer Discrimination Consistency
Yu Xi, Haoyu Li, Xiaoyu Gu +3
Connectionist Temporal Classification (CTC), a non-autoregressive training criterion, is widely used in online keyword spotting (KWS). However, existing CTC-based KWS decoding stra…
NTC-KWS: Noise-aware CTC for Robust Keyword Spotting
Yu Xi, Haoyu Li, Hao Li +4
In recent years, there has been a growing interest in designing small-footprint yet effective Connectionist Temporal Classification based keyword spotting (CTC-KWS) systems. They a…
A Survey on Speech Large Language Models for Understanding
Jing Peng, Yucheng Wang, Bohan Li +9
Speech understanding is essential for interpreting the diverse forms of information embedded in spoken language, including linguistic, paralinguistic, and non-linguistic cues that…
Semi-supervised Learning for Code-Switching ASR with Large Language Model Filter
Yu Xi, Wen Ding, Kai Yu +1
Code-switching (CS) phenomenon occurs when words or phrases from different languages are alternated in a single sentence. Due to data scarcity, building an effective CS Automatic S…
Text-aware Speech Separation for Multi-talker Keyword Spotting
Haoyu Li, Baochen Yang, Yu Xi +4
For noisy environments, ensuring the robustness of keyword spotting (KWS) systems is essential. While much research has focused on noisy KWS, less attention has been paid to multi-…
TDT-KWS: Fast And Accurate Keyword Spotting Using Token-and-duration Transducer
Yu Xi, Hao Li, Baochen Yang +3
Designing an efficient keyword spotting (KWS) system that delivers exceptional performance on resource-constrained edge devices has long been a subject of significant attention. Ex…
Contrastive Learning With Audio Discrimination For Customizable Keyword Spotting In Continuous Speech
Yu Xi, Baochen Yang, Hao Li +2
Customizable keyword spotting (KWS) in continuous speech has attracted increasing attention due to its real-world application potential. While contrastive learning (CL) has been wi…