A corpus of noise-induced word misperceptions for Spanish

Máté Attila Tóth, María Luisa García Lecumberri, Yan Tang, Martin Cooke

Research output: Contribution to journalArticlepeer-review

Abstract

Word misperceptions are valuable in designing and evaluating detailed computational models of speech perception, especially when a number of listeners agree on the misperceived word. The current paper describes the elicitation of a corpus of Spanish word misperceptions induced by different types of noise. Stimuli were presented using an adaptive procedure designed to promote the rapid discovery of misperceptions. The final corpus contains 3235 misperceptions along with speech and masker waveforms, permitting further experimental and modeling studies into the origin of each misperception. The corpus is available online as an open resource.

Original languageEnglish (US)
Pages (from-to)EL184-EL189
JournalJournal of the Acoustical Society of America
Volume137
Issue number2
DOIs
StatePublished - Feb 1 2015
Externally publishedYes

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Acoustics and Ultrasonics

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