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JSLHR_Oct12_Calandruccio_supplemental_materials_tableA1.pdf (246.76 kB)
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JSLHR_Oct12_Calandruccio_supplemental_materials_tableA2.pdf (392.79 kB)
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New Sentence Recognition Materials Using a Basic Non-Native English Lexicon (Calandruccio et al., 2012)
dataset
posted on 2012-10-01, 00:00 authored by Lauren Calandruccio, Rajka SmiljanicPurpose The objective of this project was to develop new sentence test materials drawing on a basic non-native English lexicon that could be used to test speech recognition for various listener populations. These materials have been designed to provide a test tool that is less linguistically biased, compared with materials that are currently available, for sentence recognition for non-native as well as native speakers of English.
Method One hundred non-native speakers of English were interviewed on a range of 20 conversational topics. Over 26 hr of recorded non-native English speech were transcribed. These transcriptions were used to create a lexicon of over 4,000 unique words. The words from this lexicon were used to create the new materials based on a simple syntactic sentence structure frame.
Results Twenty lists of 25 sentences were developed. Each sentence has 4 keywords, providing 100 keywords per list. Lists were equated for rate of occurrence of keywords in lexicon, high-frequency count (total number of affricates and fricatives), number of syllables, and distribution of syntactic structure. Listening-in-noise results for native-English-speaking, normal-hearing listeners indicated similar performance across lists.
Conclusion The Basic English Lexicon materials provide a large set of sentences for native and non-native English speech-recognition testing.
Method One hundred non-native speakers of English were interviewed on a range of 20 conversational topics. Over 26 hr of recorded non-native English speech were transcribed. These transcriptions were used to create a lexicon of over 4,000 unique words. The words from this lexicon were used to create the new materials based on a simple syntactic sentence structure frame.
Results Twenty lists of 25 sentences were developed. Each sentence has 4 keywords, providing 100 keywords per list. Lists were equated for rate of occurrence of keywords in lexicon, high-frequency count (total number of affricates and fricatives), number of syllables, and distribution of syntactic structure. Listening-in-noise results for native-English-speaking, normal-hearing listeners indicated similar performance across lists.
Conclusion The Basic English Lexicon materials provide a large set of sentences for native and non-native English speech-recognition testing.
