Chapter

Advances in Neural Networks – ISNN 2007

Volume 4491 of the series Lecture Notes in Computer Science pp 1318-1326

Zero-Crossing-Based Feature Extraction for Voice Command Systems Using Neck-Microphones

  • Sang Kyoon ParkAffiliated withCarnegie Mellon UniversityDivision of Applied Mathematics, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701
  • , Rhee Man KilAffiliated withCarnegie Mellon UniversityDivision of Applied Mathematics, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701
  • , Young-Giu JungAffiliated withCarnegie Mellon UniversitySmart Interface Research Team, Electronics and Telecommunications Research Institute, 161 Gajeong-dong, Yuseong-gu, Daejeon 305-700
  • , Mun-Sung HanAffiliated withCarnegie Mellon UniversitySmart Interface Research Team, Electronics and Telecommunications Research Institute, 161 Gajeong-dong, Yuseong-gu, Daejeon 305-700

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Abstract

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.