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Close/distant talker discrimination based on kurtosis of linear prediction residual signals

Desired/undesired speech discrimination is as important as speech/non-speech discrimination to achieve useful applications such as speech interfaces and teleconferencing systems. Conventional methods of voice activity detection (VAD) utilize the directional information of sound sources to distinguish desired from undesired speech. However, these methods have to utilize multiple microphones to estimate the directions of sound sources. Here, we propose a new method to discriminate desired from undesired speech with a single microphone. We assumed that the desired talkers would be close to the microphone, and the proposed method could distinguish close/distant-talking speech from observed signals based on the kurtosis of the linear prediction (LP) residual signals. The experimental results revealed that the proposed method could distinguish close-talking speech from distant-talking speech within a 10% equal error rate (EER) in ordinary reverberant environments with less processing time.