Quantitative Analysis of Audio-Visual Tasks: An Information-Theoretic Perspective

TL;DR

This paper applies information theory to quantitatively analyze audio-visual speech tasks, revealing insights into the challenges and benefits of modality integration in spoken language processing.

Contribution

It introduces a novel information-theoretic framework for analyzing audio-visual tasks, addressing the lack of theoretical understanding in this area.

Findings

Information intersection explains task difficulties.

Modality integration offers significant benefits.

Analysis guides future audio-visual research.

Abstract

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.