April 22, 2024, 4:42 a.m. | Zhaoxi Mu, Xinyu Yang

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.12725v1 Announce Type: cross
Abstract: The integration of visual cues has revitalized the performance of the target speech extraction task, elevating it to the forefront of the field. Nevertheless, this multi-modal learning paradigm often encounters the challenge of modality imbalance. In audio-visual target speech extraction tasks, the audio modality tends to dominate, potentially overshadowing the importance of visual guidance. To tackle this issue, we propose AVSepChain, drawing inspiration from the speech chain concept. Our approach partitions the audio-visual target speech …

abstract arxiv audio challenge cs.cv cs.lg cs.mm cs.sd eess.as extraction integration modal multi-modal paradigm performance speech tasks type visual visual cues

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Lead Data Modeler

@ Sherwin-Williams | Cleveland, OH, United States