کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
926528 921875 2011 28 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A computational model of word segmentation from continuous speech using transitional probabilities of atomic acoustic events
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
A computational model of word segmentation from continuous speech using transitional probabilities of atomic acoustic events
چکیده انگلیسی

Word segmentation from continuous speech is a difficult task that is faced by human infants when they start to learn their native language. Several studies indicate that infants might use several different cues to solve this problem, including intonation, linguistic stress, and transitional probabilities between subsequent speech sounds. In this work, a computational model for word segmentation and learning of primitive lexical items from continuous speech is presented. The model does not utilize any a priori linguistic or phonemic knowledge such as phones, phonemes or articulatory gestures, but computes transitional probabilities between atomic acoustic events in order to detect recurring patterns in speech. Experiments with the model show that word segmentation is possible without any knowledge of linguistically relevant structures, and that the learned ungrounded word models show a relatively high selectivity towards specific words or frequently co-occurring combinations of short words.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Cognition - Volume 120, Issue 2, August 2011, Pages 149–176
نویسندگان
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