Multimodal signal processing is a research field concerned with the theoretical and methodological principles for acquiring, representing, analyzing, and integrating data streams originating from multiple distinct sensing modalities. It focuses on leveraging complementary or correlated information across diverse sources, such as audio, visual, textual, or physiological signals, to enhance understanding, improve system performance, and enable capabilities not achievable with unimodal analysis.