6 citations · 6 across the 15 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…
WeSep: A Modular and Cue-Composable Framework for Target Speaker Extraction
Ke Zhang, Xiaoyang Yu, Haoyu Li +3
The study of Target Speaker Extraction (TSE) aims to isolate a desired speaker from overlapping speech mixture given auxiliary cues. Existing systems are typically designed for spe…
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…
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…
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…
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…
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…