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Relative Transfer Function Estimation from Speech Keywords

  • Ryan M. Corey
  • Andrew C. Singer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10891)

Abstract

Far-field speech capture systems rely on microphone arrays to spatially filter sound, attenuating unwanted interference and noise and enhancing a speech signal of interest. To design effective spatial filters, we must first estimate the acoustic transfer functions between the source and the microphones. It is difficult to estimate these transfer functions if the source signals are unknown. However, in systems that are activated by a particular speech phrase, we can use that phrase as a pilot signal to estimate the relative transfer functions. Here, we propose a method to estimate relative transfer functions from known speech phrases in the presence of background noise and interference using template matching and time-frequency masking. We find that the proposed method can outperform conventional estimation techniques, but its performance depends on the characteristics of the speech phrase.

Keywords

Relative transfer function Multichannel source separation Keyword spotting Microphone array 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of Illinois at Urbana-ChampaignUrbanaUSA

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