Spoken Word Recognition by Humans: A Single- or a Multi-Layer Process

Abstract

This 7-month-long project quantifies the role of brain rhythms in speech perception by measuring intelligibility of spoken sentences with judiciously manipulated changes in syllabic rhythm. Speech was time-compressed by a factor of three, resulting in a signal with a syllabic rate three times faster than the original and with poor intelligibility (< 50% words correct). An artificial "syllabic" rate was then introduced by segmenting the time-compressed speech signal into consecutive 40-ms intervals, each followed by a variable interval of silence. The parameters of interest were the length of the silent intervals inserted (ranging between 0-160 ms) and whether the intervals were equal in length (i.e., periodic) or not (i.e., aperiodic). The resulting performance curve is U-shaped, with best intelligibility measured at silence interval of 80 ms inserted periodically. This is also the condition in which there is a significant difference in intelligibility between periodic and aperiodic insertion (the error rate of the latter is nearly twice as high). The U-shaped performance curve may reflect the operation of cortical rhythms. Optimum intelligibility is associated with waveform-energy fluctuations in the core of the theta range of neural oscillations (3-8 Hz), which is also the core range of syllabic rate in naturally spoken utterances. Poor intelligibility may reflect the mismatch between waveform-energy fluctuations and theta rhythms in the brain.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2008
Accession Number
ADA479257

Entities

People

  • Oded Ghitza

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Brain
  • Central Nervous System
  • Contracts
  • Frequency
  • Information Processing
  • Intelligibility
  • Language
  • Nervous System
  • Oscillation
  • Perception
  • Recognition
  • Speech
  • Speech Compression
  • Syllables
  • Training
  • Waveforms
  • Word Recognition

Readers

  • Regression Analysis.
  • Speech Processing/Speech Recognition.