Sound interval detection of multiple sources based on sound directivity

Utterance interval detection is a bottleneck for the current speech recognition performance in robots embedded in real noisy environments. In the present work, we make use of sound localization technology using a microphone array, not only for localizing, but also for detecting sound intervals of multiple sound sources. In our previous work we have implemented and evaluated sound localization in the 3D-space using the MUSIC (MUltiple SIgnal Classification) method. In the present work, we proposed a method for detecting sound intervals based on the sound directivity information inferred from the dynamics of the MUSIC spectrogram. The proposed method achieved high sound interval detection accuracies and low insertion rates compared with the previous sound localization results.