Papers by Wenxi Li
Enhancing Speech-to-Speech Dialogue Modeling with End-to-End Retrieval-Augmented Generation (2025.findings-emnlp)
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| Challenge: | End-to-end speech-to speech (S2S) dialogue systems face key challenges in incorporating external knowledge into their models. |
| Approach: | They propose a framework that directly retrieves relevant textual knowledge from speech queries. |
| Outcome: | The proposed framework improves the performance of end-to-end speech-tospeech dialogue systems while achieving higher retrieval efficiency. |
FineLAP: Taming Heterogeneous Supervision for Fine-grained Language-Audio Pretraining (2026.acl-long)
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| Challenge: | Existing audio-language models excel at clip-level understanding but struggle with frame-level tasks. |
| Approach: | They propose a novel training paradigm that advances both clip- and frame-level alignment in CLAP with heterogeneous data. |
| Outcome: | The proposed training paradigm improves both clip- and frame-level alignment in CLAP with heterogeneous data. |
SAC: Neural Speech Codec with Semantic-Acoustic Dual-Stream Quantization (2026.acl-long)
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Wenxi Chen, Ruiqi Yan, Yushen Chen, Zhikang Niu, Ziyang Ma, Xiquan Li, Yuzhe Liang, null Wenhanlin, Shunshun Yin, Ming Tao, Xinsheng Wang, Xie Chen
| Challenge: | Existing speech codecs struggle to balance high-quality reconstruction with semantically rich representations, limiting their effectiveness in both generative and understanding tasks. |
| Approach: | They propose a neural speech codec with semantic-acoustic dual-stream quantization that disentangles semantic and acousian modeling into two dedicated streams. |
| Outcome: | The proposed codec outperforms state-of-the-art speech tokenizers in auto-propagating text-to-speech models. |
MeanAudio: Fast and Faithful Text-to-Audio Generation with Mean Flows (2026.acl-long)
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| Challenge: | Recent advances in Text-to-Audio Generation (TTA) systems suffer from slow inference speed, authors report . authors demonstrate that MeanAudia achieves state-of-the-art performance in single-step audio generation . |
| Approach: | They propose a text-to-audio generator capable of rendering realistic sound with only one function evaluation. |
| Outcome: | The proposed system achieves state-of-the-art performance in single-step audio generation. |
Universal Semantic Tagging for English and Mandarin Chinese (2021.naacl-main)
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| Challenge: | Existing approaches to generating semantic annotations for different languages are attracting more and more interest. |
| Approach: | They propose to extend Universal Semantic Tagging to Mandarin Chinese and evaluate its performance. |
| Outcome: | The proposed scheme is only tested in four Indo–European languages . accuracies are 92.7% and 94.6% for Chinese and English respectively . |
Towards Reliable Large Audio Language Model (2025.findings-acl)
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Ziyang Ma, Xiquan Li, Yakun Song, Wenxi Chen, Chenpeng Du, Jian Wu, Yuanzhe Chen, Zhuo Chen, Yuping Wang, Yuxuan Wang, Xie Chen
| Challenge: | Recent advances in large audio language models (LALMs) have demonstrated impressive results and promising prospects in universal understanding and reasoning across speech, music, and general sound. |
| Approach: | They propose to use training-free and training-based methods to enhance LALM reliability to different extents. |
| Outcome: | The proposed methods improve the reliability of large audio language models to different extents. |
SLAM-Omni: Timbre-Controllable Voice Interaction System with Single-Stage Training (2025.findings-acl)
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Wenxi Chen, Ziyang Ma, Ruiqi Yan, Yuzhe Liang, Xiquan Li, Ruiyang Xu, Zhikang Niu, Yanqiao Zhu, Yifan Yang, Zhanxun Liu, Kai Yu, Yuxuan Hu, Jinyu Li, Yan Lu, Shujie Liu, Xie Chen
| Challenge: | a new spoken dialogue system with single-stage training is demonstrating its low latency and high quality . SLAM-Omni achieves zero-shot timbre control by modeling spoken language with semantic tokens . |
| Approach: | They propose a timbre-controllable, end-to-end voice interaction system with single-stage training. |
| Outcome: | The proposed system outperforms previous models on 4 GPUs with limited data. |
Compositional Syntactico-SemBanking for English as a Second or Foreign Language (2025.findings-acl)
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| Challenge: | Despite the widespread use of English as a Second or Foreign Language (ESFL), developing syntactico-semantic representations for it is limited. |
| Approach: | They propose a Synchronous Hyperedge Replacement Grammar-based constructivist approach to address the challenges in ESFL. |
| Outcome: | The proposed approach bridges the gap between literal cues and intended meaning by using constructions as fundamental units. |
On the Continued Value of Universal Dependencies in the Era of Large Language Models (2026.acl-long)
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| Challenge: | a growing belief that explicit linguistic representations are no longer necessary is questioned in large language models . a recent study examines whether and in what ways this cross-lingual syntactic framework can still benefit LLMs . |
| Approach: | They use Universal Dependencies (UD) to examine whether and in what ways it can still benefit LLMs. |
| Outcome: | The proposed model outperforms its syntax-agnostic counterparts in a cross-lingual evaluation task. |
URO-Bench: Towards Comprehensive Evaluation for End-to-End Spoken Dialogue Models (2025.findings-emnlp)
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| Challenge: | a lack of comprehensive evaluations for SDMs in speech-to-speech (S2S) scenarios is a major challenge for end-to end spoken dialogue models. |
| Approach: | They propose to provide an extensive evaluation framework for end-to-end spoken dialogue models (SDMs) that includes both cognitive dimensions and paralinguistic cues . |
| Outcome: | The proposed benchmark is divided into two difficulty levels: basic track and pro track, each comprising 20 test sets, evaluating the spoken dialogue model’s abilities in U**nderstanding, **R**easoning, and **O**ral conversation. |