Representation of phonemes in primary auditory cortex: How the brain analyzes speech

Nima Mesgarani, Stephen David, Shihab Shamma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

28 Scopus citations

Abstract

Many transformations inspired by the auditory system have improved the performance of Automatic Speech Recognition (ASR) systems. However, humans perform substantially better than today's ASR systems, suggesting that ASR systems can further benefit from understanding how the brain represents speech. To learn about the cortical representation of speech, we measured the neural responses in the primary auditory cortex to sentences from the TIMIT database. Here we examine how individual phonemes activate different subsets of auditory neurons, reflecting the diversity of neural tuning properties. We find that neurons with different spectro-temporal tuning provide an explicit multidimensional representation of articulatory features independent of speaker and context. This representation that matches the human perception could provide a framework for ASR in adverse conditions.

Original languageEnglish (US)
Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages765-768
Number of pages4
ISBN (Print)1424407281, 9781424407286
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
Duration: Apr 15 2007Apr 20 2007

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
ISSN (Print)1520-6149

Other

Other2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Country/TerritoryUnited States
CityHonolulu, HI
Period4/15/074/20/07

Keywords

  • Auditory system
  • Speech processing
  • Speech recognition

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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