Quantitative Analysis of Audio-Visual Tasks: An Information-Theoretic Perspective
원문 초록
In the field of spoken language processing, audio-visual speech processing is receiving increasing research attention. Key components of this research include tasks such as lip reading, audio-visual speech recognition, and visual-to-speech synthesis. Although significant success has been achieved, theoretical analysis is still insufficient for audio-visual tasks. This paper presents a quantitative analysis based on information theory, focusing on information intersection between different modalities. Our results show that this analysis is valuable for understanding the difficulties of audio-visual processing tasks as well as the benefits that could be obtained by modality integration.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
SwinLip: An Efficient Visual Speech Encoder for Lip Reading Using Swin Transformer
Chinese-LiPS: A Chinese audio-visual speech recognition dataset with Lip-reading and Presentation Slides
CoGenAV: Versatile Audio-Visual Representation Learning via Contrastive-Generative Synchronization
Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation
VisualSpeaker: Visually-Guided 3D Avatar Lip Synthesis
ViCocktail: Automated Multi-Modal Data Collection for Vietnamese Audio-Visual Speech Recognition
토론
이 논문과 연결된 포럼 글이 아직 없습니다.