title: Word Identification in Noise.
abstract: Speech intelligibility has traditionally been measured by presenting words mixed in noise to listeners for identification at several different signal-to-noise ratios. The words are produced in isolation or in sentence contexts where the predictability of specific items can be varied. Psychometric functions are typically obtained relating signal-to-noise ratio to percent correct recognition. Error analyses are often carried out by examining response confusions to construct similarity spaces for words which reflect their perceptual organisation and acoustic-phonetic similarity. When using these techniques to measure speech discrimination or speech intelligibility in an open-set format, the recognition score obtained reflects the combined influence of both the sensory information encoded in the speech signal as well as the listener's decision process and response biases. Despite this limitation, the procedure has strong face validity as a measure of word recognition performance in normal-hearing listeners as well as other clinical populations which routinely use speech audiometry techniques to diagnose and assess both peripheral and central hearing impairments. All of the major findings and phenomena in the spoken word recognition literature can be demonstrated and explored with this experimental method. This technique continues to provide extremely valuable information about the organisation of words in the mental lexicon and how these sound patterns are accessed from acoustic-phonetic information in the speech signal.
authors.affiliation: Indiana University, Bloomington, Indiana, USA.
authors.forename: David B
authors.initials: DB
authors.lastname: Pisoni