Purpose: The goal of this study was to develop and validate a new corpus of sentences without semantic context to facilitate research aimed at isolating the effects of semantic context in speech perception. Method: The newly developed corpus contains nonsensical sentences but is matched in vocabulary and syntactic structure to the existing Basic English Lexicon (BEL) corpus. It consists of 20 lists, with each list containing 25 sentences and each sentence having four keywords. Each new list contains the same keywords as the respective list in the original BEL corpus, but the keywords within each list are scrambled across sentences to eliminate semantic context within each sentence, while maintaining the original syntactic structure. All sentences in the original and nonsense BEL corpora were recorded by the same two male and two female talkers. Results: Mean intelligibility scores for each list were estimated by calculating the mean proportion of correct keywords achieved by 40 normal-hearing listeners for one male and one female talker. Although small but significant differences were found between some pairs of lists, mean performance for all 20 lists fell within the 95% confidence intervals of the mean. Conclusions: Lists in the newly developed nonsense corpus are reasonably well equated for difficulty and can be used interchangeably in a randomized experimental design. Both the original and nonsense BEL sentences, all recorded by the same four talkers, are publicly available. Supplemental Material: https://doi.org/10.23641/asha. 13022900.
Bibliographical noteFunding Information:
This work was supported by National Institute on Deafness and Other Communication Disorders Grant R01 DC012262, awarded to Andrew J. Oxenham. We thank Benjamin Munson for his advice during the development of this new corpus and for his helpful comments on an earlier version of this article.
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PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural