A study on the Method of the Keyword Spotting Recognition in the Continuous speech using Neural Network

신경 회로망을 이용한 연속 음성에서의 keyword spotting 인식 방식에 관한 연구

  • Yang, Jin-Woo (Electronic Technology Department, ChunChon Polytechnic Collage) ;
  • Kim, Soon-Hyob (Dept. of Computer Engineering & Institute of New Technology, KwangWoon University)
  • 양진우 (춘천 기능 대학 전자 기술학과) ;
  • 김순협 (광운대학교 컴퓨터공학과, 신기술 연구소)
  • Published : 1996.08.01


This research proposes a system for speaker independent Korean continuous speech recognition with 247 DDD area names using keyword spotting technique. The applied recognition algorithm is the Dynamic Programming Neural Network(DPNN) based on the integration of DP and multi-layer perceptron as model that solves time axis distortion and spectral pattern variation in the speech. To improve performance, we classify word model into keyword model and non-keyword model. We make an experiment on postprocessing procedure for the evaluation of system performance. Experiment results are as follows. The recognition rate of the isolated word is 93.45% in speaker dependent case. The recognition rate of the isolated word is 84.05% in speaker independent case. The recognition rate of simple dialogic sentence in keyword spotting experiment is 77.34% as speaker dependent, and 70.63% as speaker independent.