TY - GEN
T1 - Enabling directional human-robot speech interface via adaptive beamforming and spatial noise reduction
AU - Beh, Jounghoon
AU - Lee, Taekjin
AU - Ahn, Sungjoo
AU - Kim, Hyunsoo
AU - Han, David K.
AU - Ko, Hanseok
PY - 2007
Y1 - 2007
N2 - This paper introduces a home robot application of multi-channel based spatial noise reduction for creating human-robot speech interfaces. A microphone array is employed first to create a speech-only directional conduit, which is realized through adaptive beamforming. Through the directional conduit, the intended speech signal from the desired direction is processed for detection and recognition, while unintended speech-like-sources or undesirable noise from other angles is suppressed. If speech signal is absent among the incoming signals through the conduit, further attenuation of undesirable signals is achieved by using a spatial noise reduction filter. Experimental validation of the technique was conducted using a computer simulation and also an online Samsung AnyBot test. Although the environments exhibited highly non-stationary noise, the method achieved an average speech recognition rate of 87.4% in the case of the computer simulation and 81.6% for the online Samsung AnyBot test. From the cases tested so far, the proposed implementation seems to be effective for practical robot applications in highly non-stationary noise environment.
AB - This paper introduces a home robot application of multi-channel based spatial noise reduction for creating human-robot speech interfaces. A microphone array is employed first to create a speech-only directional conduit, which is realized through adaptive beamforming. Through the directional conduit, the intended speech signal from the desired direction is processed for detection and recognition, while unintended speech-like-sources or undesirable noise from other angles is suppressed. If speech signal is absent among the incoming signals through the conduit, further attenuation of undesirable signals is achieved by using a spatial noise reduction filter. Experimental validation of the technique was conducted using a computer simulation and also an online Samsung AnyBot test. Although the environments exhibited highly non-stationary noise, the method achieved an average speech recognition rate of 87.4% in the case of the computer simulation and 81.6% for the online Samsung AnyBot test. From the cases tested so far, the proposed implementation seems to be effective for practical robot applications in highly non-stationary noise environment.
UR - http://www.scopus.com/inward/record.url?scp=51349131380&partnerID=8YFLogxK
U2 - 10.1109/IROS.2007.4399420
DO - 10.1109/IROS.2007.4399420
M3 - Conference contribution
AN - SCOPUS:51349131380
SN - 1424409128
SN - 9781424409129
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 3454
EP - 3459
BT - Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
T2 - 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
Y2 - 29 October 2007 through 2 November 2007
ER -