On using Gaussian mixture model for double-talk detection in acoustic echo suppression

نویسندگان

  • Ji-Hyun Song
  • Kyu-Ho Lee
  • Yun-Sik Park
  • Sang-Ick Kang
  • Joon-Hyuk Chang
چکیده

In this paper, we propose a novel frequency-domain approach to double-talk detection (DTD) based on the Gaussian mixture model (GMM). In contrast to a previous approach based on a simple and heuristic decision rule utilizing time-domain crosscorrelations, GMM is applied to a set of feature vectors extracted from the frequency-domain cross-correlation coefficients. Performance of the proposed approach is evaluated through objective tests under various environments, and better results are obtained as compared to the time-domain method.

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تاریخ انتشار 2010