Robot audition is not a single technology but is a process consisting of multiple systems. There are a number of elemental technologies for component parts and in addition, component parts vary considerably in their performance. Therefore they need to interact well with each other during processing. Moreover, better interaction enables better functioning of the processes as a whole. Since the ambiguity cannot be eliminated only by acoustic treatment, integration of audiovisual information is the important key for the interaction. There are various levels of information integration, such as temporal, spatial, intermedia and intersystem integration and furthermore hierarchical information integration is required between those levels and within each level. Nakadai et al. have proposed the following audiovisual information integration. At the lowermost level, a speaker is detected from audio signals and lip movement. At the levels above, phoneme recognition and viseme recognition are integrated. At even higher levels, a speaker position and 3D position of the face are integrated. At the topmost level, speaker identification / verification and face identification / verification are integrated. Of course, not only information integration at the same level but also interactions such as bottom-up or top-down processing is possible. Generally sound mixture processing is an ill-posed problem. In order to obtain more complete solutions, it would be necessary to have some assumptions such as the assumption of sparseness. Sparseness in a time domain, sparseness in a frequency domain, sparseness in a 3D space and furthermore sparseness in a feature space are possible. Note that the success or failure of such information integration depends not only on design of the sparseness but also on performance of individual elemental technologies.