Improvement of In-Car Speech Recognition by Acoustic Echo Canceller with Maximum Likelihood

نویسندگان

  • Kentaro Koga
  • Shinji Fukuda
  • Tetsuya Takiguchi
  • Yasuo Ariki
چکیده

In this paper, as a key technology for improvement of speech recognition system in car environments, we propose an acoustic echo canceller for selecting an optimum cancellation result based on the echo estimation with maximum likelihood using transfer characteristics measured prospectively. The results of experiments conducted to speech superimposed on music show that the proposed canceller can improve S/N ratio and speech recognition rate, compared to the canceller based on the algorithm of NLMS.

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تاریخ انتشار 2008