HMM and BPNN based speech recognition system for home service robot

Chih Yin Liu, Tzu Hsin Hung, Kai Chung Cheng, Tzuu Hseng S. Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper proposes a two-stage speech recognition system based on hidden Markov model (HMM) and back-propagation neural network (BPNN) for home service robot. Since a home service robot would interact with different users, a speaker independent and robust system should be developed. The recognition system we proposed contains two learning stages to build the models of words. In the first stage, the Gaussian mixture model (GMM) likelihood probabilities are calculated by HMM. And then, the probabilities are treated as the input units of neural network in the second stage. The home service robot, May-1 is designed and implemented for realizing the speech recognition system. The experimental results show that the robot can successfully complete follow-me, recognition of names, and recognition of rooms tasks in the RoboCup@ Home league competition.

Original languageEnglish
Title of host publication2013 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2013 - Conference Proceedings
Pages38-43
Number of pages6
DOIs
Publication statusPublished - 2013 Sep 9
Event2013 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2013 - Tainan, Taiwan
Duration: 2013 May 32013 Jun 2

Publication series

Name2013 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2013 - Conference Proceedings

Other

Other2013 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2013
CountryTaiwan
CityTainan
Period13-05-0313-06-02

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

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