Skip to main content
banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
1. Christiansen, C. , Pedersen, M. S. , and Dau, T. (2010). “ Prediction of speech intelligibility based on an auditory preprocessing model,” Speech Commun. 52, 678692.
2. Cooke, M. (2006). “ A glimpsing model of speech perception in noise,” J. Acoust. Soc. Am. 119(3), 15621573.
3. Cooke, M. (2009). “ Discovering consistent word confusions in noise,” in Proceedings of Interspeech, pp. 18871890.
4. Cutler, A. , and Butterfield, S. (1992). “ Rhythmic cues to speech segmentation: Evidence from juncture misperception,” J. Mem. Lang. 31, 218236.
5. Garcia Lecumberri, M. L. , Toth, A. M. , Tang, Y. , and Cooke, M. (2013). “ Elicitation and analysis of a corpus of robust noise-induced word misperceptions in Spanish,” in Proceedings of Interspeech, pp. 28072811.
6. Garnes, S. , and Bond, Z. S. (1980). “ A slip of the ear? a snip of the ear? a slip of the year?,” in Errors in Linguistic Performance: Slips of the Tongue, Ear, Pen and Hand, edited by A. Fromkin ( Academic, New York).
7. Hernández-Figueroa, Z. , Rodríguez-Rodríguez, G. , and Carreras-Riudavets, F. (2012). Separador de sílabas del español—Silabeador TIP (Separator of Spanish syllables—Syllabifier TIP), (Last viewed September 26, 2014).
8. Holube, I. , and Kollmeier, B. (1996). “ Speech intelligibility prediction in hearing impaired listeners based on a psychoacoustically motivated perception model,” J. Acoust. Soc. Am. 100(3), 17031716.
9. Jürgens, T. , and Brand, T. (2009). “ Microscopic prediction of speech recognition for listeners with normal hearing in noise using an auditory model,” J. Acoust. Soc. Am. 126(5), 26352648.
10.REAL (2008). Corpus de referencia del español actual (A reference corpus of modern day Spanish), (Last viewed July 15, 2014).
11. Taal, C. , Hendriks, R. , Heusdens, R. , and Jensen, J. (2010). “ A short-time objective intelligibility measure for time-frequency weighted noisy speech,” in Proceedings of ICASSP, pp. 42144217.
12. Tang, K. , and Nevins, A. (2013). “ Naturalistic speech misperception—a computational corpus-based study,” in Proceedings of the 43rd Meeting of the North East Linguistic Society, New York.
13. Vitevich, M. S. (2002). “ Naturalistic and experimental analyses of word frequency and neighborhood density effects in slips of the ear,” Lang. Speech 45, 407434.

Data & Media loading...


Article metrics loading...



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.


Full text loading...


Access Key

  • FFree Content
  • OAOpen Access Content
  • SSubscribed Content
  • TFree Trial Content
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd