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Development of Voice Activity Detection Algorithm for Elderly Voice based on the Higher Order Differential Energy Operator

고차 미분에너지 기반 노인 음성에서의 음성 구간 검출 알고리즘 연구

  • Lee, JiYeoun (Department of Biomedical Engineering, Jungwon University)
  • 이지연 (중원대학교 의료공학과)
  • Received : 2016.09.29
  • Accepted : 2016.11.20
  • Published : 2016.11.28

Abstract

Since the elderly voices include a lot of noise caused by physiological changes in respiration, phonation, and resonance, the performance of the convergence health-care equipments such as speech recognition, synthesis, analysis program done by elderly voice is deteriorated. Therefore it is necessary to develop researches to operate health-care instruments with elderly voices. In this study, a voice activity detection using a symmetric higher-order differential energy function (SHODEO) was developed and was compared with auto-correlation function(ACF) and the average magnitude difference function(AMDF). It was confirmed to have a better performance than other methods in the voice interval detection. The voice activity detection will be applied to a voice interface for the elderly to improve the accessibility of the smart devices.

Keywords

Elderly voice;Auto-corration function(ACF);Average magnitude difference function(AMDF);The symmetric higher order differential energy operator(SHODEO);Voice Activity Detection

Acknowledgement

Supported by : 한국연구재단

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