A human-symbiotic robot called "EMIEW2" and its auditory function which includes two noise reduction methods against self-generated mechanical noise and external floor-level noise is introduced. The former type of noise is produced by the robot itself, and this is a difficult problem because it can be loud, non-stationary, and have a wide frequency band. We adopt a maximized SNR technique, in which noise correlation matrix is selected from noise clusters that are learned from the pre-recorded noise signals. The latter type of noise, which can occur when robots are used in office environments, is also a problem, and we addressed it by expanding the beamforming area from one dimension (azimuth angle) to the two dimensions (azimuth and elevation angles). We evaluated these methods in a 100-word speech recognition task and we show that both methods are effective for improving the speech recognition rate.
Bibliographic reference. Sumiyoshi, Takashi / Togami, Masahito / Obuchi, Yasunari (2011): "ASR for human-symbiotic robot “EMIEW2” with mechanical noise and floor-level noise reduction", In INTERSPEECH-2011, 3141-3144.