Zero-Crossing-Based Feature Extraction for Voice Command Systems Using Neck-Microphones
This paper presents zero-crossing-based feature extraction for the speech recognition using neck-microphones. One of the solutions in noise-robust speech recognition is using neck-microphones which are not affected by the environmental noises. However, neck-microphones distort the original voice signals significantly since they only capture the vibrations of vocal tracts. In this context, we consider a new method of enhancing speech features of neck-microphone signals using zero-crossings. Furthermore, for the improvement of zero-crossing features, we consider to use the statistics of two adjacent zero-crossing intervals, that is, the statistics of two samples referred to as the second order statistics. Through the simulation for speech recognition using the neck-microphone voice command system, we have shown that the suggested method provides the better performance than other approaches using conventional speech features.
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