Editing Multimodal Speech Recognition (section)

=== Data Fusion ===
The primary innovation in multimodal speech recognition is Data fusion.By merging information or data from multiple sensory modalities, such as audio, visual, tactile, and others, the speech recognition system can better comprehend and process speech input，and therefore improve recognition accuracy.  For example, the effective integration of both audio and visual cues, specifically speaker's lip images, can enhance ASR accuracy, particularly in challenging, noisy environments<ref>Tomlinson, M. J., Russell, M. J., & Brooke, N. M. (1996). Integrating audio and visual information to provide highly robust speech recognition. ''1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings'', ''2'', 821–824 vol. 2. <nowiki>https://doi.org/10.1109/ICASSP.1996.543247</nowiki></ref>. Fusing data from multiple sensory modalities even enables multimodal speech recognition systems to support more complex application scenarios, such as sign language recognition, gesture recognition, emotion analysis, and more, enhancing the system's versatility and adaptability.