An application of speech/speaker recognition system for human-robot interaction

We will introduce a real time, robust speech/speaker recognition system for isolated word recognition using distance microphone. Applying proposed system to a robot platform, robust human-robot interaction can be established for reverberant office environments. For computational effectiveness, dynamic time warping algorithm is used for pattern matching. We select the Gamma distribution contrary to the conventional Gaussian distribution to model the probability density function of total accumulated distance. By creating reference speeches at different distances, proposed algorithm shows better speech/speaker recognition performance than the case when creating reference speeches at the same distance. Experimental results show that recognition accuracy is more than 99% by creating five reference speeches at different distances in a reverberant office environment.