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Journal of Speech, Language, and Hearing Research Vol.50 270-282 April 2007. doi:10.1044/1092-4388(2007/020)
© American Speech-Language-Hearing Association

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The Consistency of Sentence Intelligibility Across Three Types of Signal Distortion

Eric W. Healy
Allen A. Montgomery

University of South Carolina, Columbia

Contact author: Eric W. Healy, Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208. E-mail: ewh{at}sc.edu.

Purpose: To examine the extent to which sentences retain their levels of spoken intelligibility relative to other sentences in a set (the sentence effect) across different types of signal distortion.

Method: The Central Institute for the Deaf (CID) sentences were rendered difficult to understand through the addition of broadband noise. These intelligibility data were compared with those from previous studies in which the sentences were distorted through filtering and visual-only conditions of speechreading. The extent to which the various sentences retained their intelligibility rankings was examined using an analysis of variance model and by correlating individual sentence means across conditions.

Results: The sentences accounted for a large portion of the variance, and individual sentence scores were highly correlated across conditions involving a single distortion type. However, correlations were lower when conditions involving noise were compared with those involving filtering. Surprisingly, correlations across auditory distortions were almost identical to those observed across auditory and visual modalities. These comparisons, reflecting the consistency of sentence difficulty independent of presentation characteristics, accounted for approximately 25% of the variance in sentence-recognition performance.

Conclusion: There exists a sentence effect that holds across various types of signal distortion, but the strongest form is restricted not only within modalities but within particular forms of distortion.

KEY WORDS: speech perception, CID sentences, speech in noise, speechreading


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