System request detection in human conversation based on multi-resolution Gabor wavelet features

Abstract

For a hands-free speech interface, it is important to detect commands in spontaneous utterances. Usual voice activity detection systems can only distinguish speech frames from nonspeech frames, but they cannot discriminate whether the detected speech section is a command for a system or not. In this paper, in order to analyze the difference between system requests and spontaneous utterances, we focus on fluctuations in a long period, such as prosodic articulation, and fluctuations in a short period, such as phoneme articulation. The use of multi-resolution analysis using Gabor wavelet on a Log-scale Mel-frequency Filter-bank clarifies the different characteristics of system commands and spontaneous utterances. Experiments using our robot dialog corpus show that the accuracy of the proposed method is 92.6% in F-measure, while the conventional power and prosody-based method is just 66.7%. Index Terms: dialog system, voice activity detection, system request detection