Abstract
The separation of speech signals measured at multiple microphones in noisy and reverberant environments using only the audio modality has limitations because there is generally insufficient information to fully discriminate the different sound sources. Humans mitigate this problem by exploiting the visual modality, which is insensitive to background noise and can provide contextual information about the audio scene. This advantage has inspired the creation of the new field of audiovisual (AV) speech source separation that targets exploiting visual modality alongside the microphone measurements in a machine. Success in this emerging field will expand the application of voice-based machine interfaces, such as Siri, the intelligent personal assistant on the iPhone and iPad, to much more realistic settings and thereby provide more natural human?machine interfaces. © 1991-2012 IEEE.
Cite
CITATION STYLE
Rivet, B., Wang, W., Naqvi, S. M., & Chambers, J. A. (2014). Audiovisual speech source separation: An overview of key methodologies. IEEE Signal Processing Magazine, 31(3), 125–134. https://doi.org/10.1109/MSP.2013.2296173
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