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20242026
most citedImproving Grapheme-to-Phoneme Conversion through In-Context Knowledge Retrieval with Large Language Models

4 citations · 14 across the 32 of their papers we have counts for

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cs.SD2025

ELEGANCE: Efficient LLM Guidance for Audio-Visual Target Speech Extraction

Wenxuan Wu, Shuai Wang, Xixin Wu +2

Audio-visual target speaker extraction (AV-TSE) models primarily rely on visual cues from the target speaker. However, humans also leverage linguistic knowledge, such as syntactic…

cs.CL2025

Naturalistic Language-related Movie-Watching fMRI Task for Detecting Neurocognitive Decline and Disorder

Yuejiao Wang, Xianmin Gong, Xixin Wu +4

Early detection is crucial for timely intervention aimed at preventing and slowing the progression of neurocognitive disorder (NCD), a common and significant health problem among t…

cs.SD2025

DiffDSR: Dysarthric Speech Reconstruction Using Latent Diffusion Model

Xueyuan Chen, Dongchao Yang, Wenxuan Wu +5

Dysarthric speech reconstruction (DSR) aims to convert dysarthric speech into comprehensible speech while maintaining the speaker's identity. Despite significant advancements, exis…

cs.CL2025

RAG-Zeval: Towards Robust and Interpretable Evaluation on RAG Responses through End-to-End Rule-Guided Reasoning

Kun Li, Yunxiang Li, Tianhua Zhang +4

Robust evaluation is critical for deploying trustworthy retrieval-augmented generation (RAG) systems. However, current LLM-based evaluation frameworks predominantly rely on directl…

cs.SD2025

ALMTokenizer: A Low-bitrate and Semantic-rich Audio Codec Tokenizer for Audio Language Modeling

Dongchao Yang, Songxiang Liu, Haohan Guo +9

Recent advancements in audio language models have underscored the pivotal role of audio tokenization, which converts audio signals into discrete tokens, thereby facilitating the ap…

cs.CL2025

Generate, Discriminate, Evolve: Enhancing Context Faithfulness via Fine-Grained Sentence-Level Self-Evolution

Kun Li, Tianhua Zhang, Yunxiang Li +5

Improving context faithfulness in large language models is essential for developing trustworthy retrieval augmented generation systems and mitigating hallucinations, especially in…