Recovering sound sources from embedded repetition

Josh H. McDermott, David Wrobleski, Andrew J. Oxenham

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

Abstract

Cocktail parties and other natural auditory environments present organisms with mixtures of sounds. Segregating individual sound sources is thought to require prior knowledge of source properties, yet these presumably cannot be learned unless the sources are segregated first. Here we show that the auditory system can bootstrap its way around this problem by identifying sound sources as repeating patterns embedded in the acoustic input. Due to the presence of competing sounds, source repetition is not explicit in the input to the ear, but it produces temporal regularities that listeners detect and use for segregation. We used a simple generative model to synthesize novel sounds with naturalistic properties. We found that such sounds could be segregated and identified if they occurred more than once across different mixtures, even when the same sounds were impossible to segregate in single mixtures. Sensitivity to the repetition of sound sources can permit their recovery in the absence of other segregation cues or prior knowledge of sounds, and could help solve the cocktail party problem.

Original languageEnglish (US)
Pages (from-to)1188-1193
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume108
Issue number3
DOIs
StatePublished - Jan 18 2011

Keywords

  • Auditory scene analysis
  • Cocktail party problem
  • Generative models of sound
  • Natural sound statistics
  • Sound segregation

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