Double-talk detector based on speech feature extraction for acoustic echo cancellation
Mahfoud Hamidia, Abderrahmane Amrouche · 2014
This paper presents a new method of the Double Talk Detection (DTD) for acoustic echo cancellation. The main goal is to remove the undesirable acoustic echoes produced by the coupling between the loudspeaker and the microphone of the mobile station. Acoustic Echo Canceller (AEC) based on adaptive filtering is an attractive solution. In this work, DTD using discriminative speech feature extraction from the near-end and the microphone speech signals was performed. The main purpose is to discriminate between these signals for sensing Double Talk (DT) periods. To evaluate the performance we use the NLMS algorithm to update the filter coefficients. Results obtained from the TIMIT database show that the performances of the proposed method are significantly improved, compared to the Normalized Cross Correlation (NCC) and Geigel methods.