Isolating the Energetic Component of Speech-on-Speech Masking With Ideal Time-Frequency Segregation

Abstract

When a target speech signal is obscured by an interfering speech wave form, comprehension of the target message depends both on the successful detection of the energy from the target speech wave form and on the successful extraction and recognition of the spectro-temporal energy pattern of the target out of a background of acoustically similar masker sounds. This study attempted to isolate the effects that energetic masking, defined as the loss of detectable target information due to the spectral overlap of the target and masking signals, has on multi-talker speech perception. This was achieved through the use of ideal time-frequency binary masks that retained those spectro-temporal regions of the acoustic mixture that were dominated by the target speech but eliminated those regions that were dominated by the interfering speech. The results suggest that energetic masking plays a relatively small role in the overall masking that occurs when speech is masked by interfering speech but a much more significant role when speech is masked by interfering noise.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2006
Accession Number
ADA498493

Entities

People

  • Brian D. Simpson
  • DeLiang Wang
  • Douglas S. Brungart
  • Peter S. Chang

Organizations

  • Air Force Research Laboratory

Tags

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Automated Speech Recognition
  • Cognitive Science
  • Computer Science
  • Computers
  • Detection
  • Frequency
  • Frequency Bands
  • Human Factors Engineering
  • Identification
  • Intelligibility
  • Psychology
  • Recognition
  • Signal Processing
  • Speech
  • Waveforms

Readers

  • Sensor Fusion and Tracking Systems.
  • Speech Processing/Speech Recognition.