Spatial filter calibration based on minimization of modified LSD

A new sound source separation method has been developed that is robust against individual variability in microphones and acoustic lines. A specific area that has a target sound source was enhanced by using a spatial filter developed by time-frequency masking. However, there is a strong likelihood that the spatial filters will be distorted due to the impact of individual variability in microphone characteristics and acoustic lines. To solve this problem, calibration of these spatial filters' shapes was attempted using a modified log-spectral distance (MLSD) minimization criterion, which uses utterances made by each individual (i.e., a sound source) at the desired positions. The effectiveness of this spatial filter calibration was experimentally verified in speech recognition experiments; MLSD-based calibration had fewer word errors than the cases without calibration and calibration using other criteria.