title: Using statistical decision theory to predict speech intelligibility. II. Measurement and prediction of consonant-discrimination performance.
abstract: The speech recognition sensitivity (SRS) model [H. Müsch and S. Buus, J. Acoust. Soc. Am. 109, 2896-2909 (2001)] was tested by applying it to consonant-discrimination data collected in this study. Normally hearing listeners' abilities to discriminate among 18 consonants were measured in 58 filter conditions using two test paradigms. In one paradigm, listeners chose among all 18 stimuli. In the other, response alternatives were restricted to the correct response and eight consonants that were randomly selected among the 17 incorrect response alternatives. The effect of the number of response alternatives on performance can be described by statistical decision theory. Most filter conditions included one or more sharply filtered narrow bands of speech. Depending on the selection of bands, listeners' performance in multi-band conditions falls short of, equals, or exceeds the performance expected from multiplication of the error rates in the individual bands. The performance advantage in multi-band conditions increases with average band separation. The SRS model provides a good fit to the data and predicts the data more accurately than does the speech intelligibility index.
authors: Communications and Digital Signal Processing Center, Department of Electrical and Computer Engineering, Northeastern University, Boston, Massachusetts 02115, USA.
authors: H
authors: H
authors: Müsch
authors: S
authors: S
authors: Buus
mesh_terms: D000328:Adult; D003657:Decision Making; D004192:Discrimination, Psychological; D005260:Female; D005544:Forecasting; D006801:Humans; D008960:Models, Psychological; D010700:Phonetics; D011582:Psychological Theory; D013060:Speech / Q000502:physiology*; D013065:Speech Intelligibility; D013067:Speech Perception / Q000502:physiology*