activity
20242026
most citedLarge Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition

10 citations · 15 across the 17 of their papers we have counts for

collaborators

17 papers

cs.SD2026

Disentangling Acoustic Cues in Alzheimer's Pathology and Perception: The Roles of Language and Gender

Liu He, Yuanchao Li, Yin-Long Liu +5

Acoustic biomarkers show promise for detecting Alzheimer's Disease (AD), yet whether the cues driving diagnostic AI align with those salient to human listeners is underexplored acr…

eess.AS2026

CoSTA: Cognitive-State-Conditioned TTS Data Augmentation Using ASR Transcripts for Alzheimer's Disease Detection

Yin-Long Liu, Yuanchao Li, Yiming Wang +8

Speech-based Alzheimer's Disease (AD) detection is constrained by scarce pathological speech data. To address this, we propose CoSTA, a Text-to-Speech (TTS)-based data augmentation…

cs.CV2026

AVI-Bench: Toward Human-like Audio-Visual Intelligence of Omni-MLLMs

Yaoting Wang, Ziyi Zhang, Wenming Tu +10

Recent advances in Omni-Multimodal Large Language Models (Omni-MLLMs) have enabled strong integration of vision, audio, and language. However, their audio-visual intelligence (AVI)…

eess.AS2026

AdaLTM: Adaptive Layer-wise Task Vector Merging for Categorical Speech Emotion Recognition with ASR Knowledge Integration

Chia-Yu Lee, Huang-Cheng Chou, Tzu-Quan Lin +4

Integrating Automatic Speech Recognition (ASR) into Speech Emotion Recognition (SER) enhances modeling by providing linguistic context. However, conventional feature fusion faces p…

eess.AS2026

Speech Emotion Recognition with ASR Integration

Yuanchao Li

Speech Emotion Recognition (SER) plays a pivotal role in understanding human communication, enabling emotionally intelligent systems, and serving as a fundamental component in the…

cs.CL2025

Exploring Gender Bias in Alzheimer's Disease Detection: Insights from Mandarin and Greek Speech Perception

Liu He, Yuanchao Li, Rui Feng +5

Gender bias has been widely observed in speech perception tasks, influenced by the fundamental voicing differences between genders. This study reveals a gender bias in the percepti…

eess.AS2025

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech

Yin-Long Liu, Yuanchao Li, Rui Feng +7

This paper presents our submission to the PROCESS Challenge 2025, focusing on spontaneous speech analysis for early dementia detection. For the three-class classification task (Hea…

eess.AS2025

Segmentation-Variant Codebooks for Preservation of Paralinguistic and Prosodic Information

Nicholas Sanders, Yuanchao Li, Korin Richmond +1

Quantization in SSL speech models (e.g., HuBERT) improves compression and performance in tasks like language modeling, resynthesis, and text-to-speech but often discards prosodic a…

cs.CL2024★ 10 cited

Large Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition

Chao-Han Huck Yang, Taejin Park, Yuan Gong +18

Given recent advances in generative AI technology, a key question is how large language models (LLMs) can enhance acoustic modeling tasks using text decoding results from a frozen,…

eess.AS2024

Exploring Acoustic Similarity in Emotional Speech and Music via Self-Supervised Representations

Yujia Sun, Zeyu Zhao, Korin Richmond +1

Emotion recognition from speech and music shares similarities due to their acoustic overlap, which has led to interest in transferring knowledge between these domains. However, the…

eess.AS2024

Semi-Supervised Cognitive State Classification from Speech with Multi-View Pseudo-Labeling

Yuanchao Li, Zixing Zhang, Jing Han +2

The lack of labeled data is a common challenge in speech classification tasks, particularly those requiring extensive subjective assessment, such as cognitive state classification.…

eess.AS2024★ 2 cited

Cross-Lingual Speech Emotion Recognition: Humans vs. Self-Supervised Models

Zhichen Han, Tianqi Geng, Hui Feng +3

Utilizing Self-Supervised Learning (SSL) models for Speech Emotion Recognition (SER) has proven effective, yet limited research has explored cross-lingual scenarios. This study pre…

eess.AS2024★ 1 cited

Revise, Reason, and Recognize: LLM-Based Emotion Recognition via Emotion-Specific Prompts and ASR Error Correction

Yuanchao Li, Yuan Gong, Chao-Han Huck Yang +2

Annotating and recognizing speech emotion using prompt engineering has recently emerged with the advancement of Large Language Models (LLMs), yet its efficacy and reliability remai…

eess.AS2024

Addressing Emotion Bias in Music Emotion Recognition and Generation with Frechet Audio Distance

Yuanchao Li, Azalea Gui, Dimitra Emmanouilidou +1

The complex nature of musical emotion introduces inherent bias in both recognition and generation, particularly when relying on a single audio encoder, emotion classifier, or evalu…

cs.CV2024★ 1 cited

Can Textual Semantics Mitigate Sounding Object Segmentation Preference?

Yaoting Wang, Peiwen Sun, Yuanchao Li +2

The Audio-Visual Segmentation (AVS) task aims to segment sounding objects in the visual space using audio cues. However, in this work, it is recognized that previous AVS methods sh…

eess.AS2024

Speech Emotion Recognition with ASR Transcripts: A Comprehensive Study on Word Error Rate and Fusion Techniques

Yuanchao Li, Peter Bell, Catherine Lai

Text data is commonly utilized as a primary input to enhance Speech Emotion Recognition (SER) performance and reliability. However, the reliance on human-transcribed text in most s…

cs.HC2024★ 1 cited

Beyond Voice Assistants: Exploring Advantages and Risks of an In-Car Social Robot in Real Driving Scenarios

Yuanchao Li, Lachlan Urquhart, Nihan Karatas +3

In-car Voice Assistants (VAs) play an increasingly critical role in automotive user interface design. However, existing VAs primarily perform simple 'query-answer' tasks, limiting…