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Dual-Channel Cosine Function Based ITD Estimation for Robust Speech Separation.

Xuliang Li1, Zhaogui Ding2, Weifeng Li3

  • 1Department of Electronic Engineering/Graduate School at Shenzhen, Tsinghua University, Beijing 100084, China. 64795992@163.com.

Sensors (Basel, Switzerland)
|June 21, 2017
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Summary
This summary is machine-generated.

This study introduces a new two-microphone speech separation method overcoming limitations of closely spaced microphones. The technique uses interaural time difference (ITD) and time-frequency masks for effective speech source separation.

Keywords:
binary time-frequency maskcosine functiondelay-and-sum beamforming

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Area of Science:

  • Acoustics
  • Signal Processing
  • Computational Auditory Scene Analysis

Background:

  • Traditional speech separation methods often require closely spaced microphones, limiting their application due to phase wrap-around issues.
  • Existing techniques struggle with accurate separation when microphone spacing is not optimal.

Purpose of the Study:

  • To propose a novel speech separation scheme using two microphones that is not restricted by microphone spacing.
  • To address the limitations of existing methods in handling phase wrap-around in speech separation.

Main Methods:

  • The proposed method estimates interaural time difference (ITD) statistics and utilizes a binary time-frequency mask for separating mixed speech sources.
  • Extended application of delay-and-sum beamforming (DSB) and cosine function for ITD calculation.
  • Clarification of the relationship between the ideal binary mask and the DSB amplitude ratio.

Main Results:

  • Objective quality evaluation experiments confirm the effectiveness of the proposed speech separation method.
  • The technique successfully separates mixed speech sources without the constraint of closely spaced microphones.

Conclusions:

  • The novel speech separation scheme effectively separates mixed speech sources using two microphones, overcoming the limitations of microphone spacing.
  • The method's reliance on ITD statistics and time-frequency masks offers a robust solution for real-world acoustic environments.