activity
20242026
collaborators

7 papers

cs.LG2026

Asymmetric Hierarchical Anchoring for Robust Audio-Visual Cross-Modal Generalization

Bixing Wu, Yuhong Zhao, Zongli Ye +3

Audio-visual joint representation learning under Cross-Modal Generalization (CMG) aims to transfer knowledge from a labeled source modality to an unlabeled target modality through…

cs.CV2025

VideoCanvas: Unified Video Completion from Arbitrary Spatiotemporal Patches via In-Context Conditioning

Minghong Cai, Qiulin Wang, Zongli Ye +7

Existing controllable video generation methods are typically designed for rigid, task-specific settings, such as first-frame image-to-video, inpainting, or interpolation, treating…

cs.MM2025

AV-EMO-Reasoning: Benchmarking Emotional Reasoning Capabilities in Omni-modal LLMS with Audio-visual Cues

Dingkun Zhou, Krish Patel, Ajay Kankipati +14

Emotions conveyed through voice and face shape engagement and context in human AI interaction. Despite rapid progress in omni modal large language models, the holistic evaluation o…

eess.AS2025

LCS-CTC: Leveraging Soft Alignments to Enhance Phonetic Transcription Robustness

Zongli Ye, Jiachen Lian, Akshaj Gupta +18

Phonetic speech transcription is crucial for fine-grained linguistic analysis and downstream speech applications. While Connectionist Temporal Classification (CTC) is a widely used…

eess.AS2025

Seamless Dysfluent Speech Text Alignment for Disordered Speech Analysis

Zongli Ye, Jiachen Lian, Xuanru Zhou +14

Accurate alignment of dysfluent speech with intended text is crucial for automating the diagnosis of neurodegenerative speech disorders. Traditional methods often fail to model pho…

eess.AS2025

Dysfluent WFST: A Framework for Zero-Shot Speech Dysfluency Transcription and Detection

Chenxu Guo, Jiachen Lian, Xuanru Zhou +13

Automatic detection of speech dysfluency aids speech-language pathologists in efficient transcription of disordered speech, enhancing diagnostics and treatment planning. Traditiona…

eess.AS2024

Time and Tokens: Benchmarking End-to-End Speech Dysfluency Detection

Xuanru Zhou, Jiachen Lian, Cheol Jun Cho +10

Speech dysfluency modeling is a task to detect dysfluencies in speech, such as repetition, block, insertion, replacement, and deletion. Most recent advancements treat this problem…