Wake-up-word spotting for mobile systems

Wake-up-word (WUW) spotting for mobile devices has attracted much attention recently. The aim is to detect the occurrence of very few or only one personalized keyword in a continuous potentially noisy audio signal. The application in personal mobile devices is to activate the device or to trigger an alarm in hazardous situations by voice. In this paper, we present a low-resource approach and results for WUW spotting based on template matching using dynamic time warping and other measures. The recognition of the WUW is performed by a combination of distance measures based on a simple background noise level classification. For evaluation we recorded a WUW spotting database with three different background noise levels, four different speaker distances to the microphone, and ten different speakers. It consists of 480 keywords embedded in continuous audio data.