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- W1623245510 abstract "Reasoning about sound similarities improves the performance of a Natural Language Understanding component that interprets speech recognizer output: the authors observed a 5% to 7% reduction in errors when they augmented the word strings with a phonetic representation, derived from the words by means of a dictionary. The best performance comes from mixture models incorporating both word and phone features. Since the phonetic representation is derived from a dictionary, the method can be applied easily without the need for integration with a specific speech recognizer. The method has similarities with autonomous (or bottom-up) psychological models of lexical access, where contextual information is not integrated at the stage of auditory perception but rather later." @default.
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- W1623245510 date "2012-02-29" @default.
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- W1623245510 title "Improving Spoken Dialogue Understanding Using Phonetic Mixture Models" @default.
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- W1623245510 doi "https://doi.org/10.4018/978-1-61350-447-5.ch015" @default.
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