Dia AbuZeina's Cross-Word Modeling for Arabic Speech Recognition PDF

By Dia AbuZeina

ISBN-10: 1461412129

ISBN-13: 9781461412120

ISBN-10: 1461412137

ISBN-13: 9781461412137

Cross-Word Modeling for Arabic Speech Recognition makes use of phonological ideas as a way to version the cross-word challenge, a merging of adjoining phrases in speech attributable to non-stop speech, to reinforce the functionality of constant speech reputation structures. the writer goals to supply an realizing of the cross-word challenge and the way it may be kept away from, particularly targeting Arabic phonology utilizing an HHM-based classifier.

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2007) proposed a three-stage framework for Mandarin Chinese to construct automatically the multiple-pronunciation dictionary while reducing the possible confusion caused. Even though cross-word phenomenon has been widely investigated for English, research works have been found in other languages. AbuZeina et al. (2011) presented a method to model cross-word problem using a set of Arabic phonological rules. Kessens et al. (1999) investigated two approaches to model the crossword problem for Dutch.

They contain the phonetic transcriptions of all the vocabulary in the target domain of the conversation. A phonetic transcription is a sequence of phonemes that describes how the corresponding word should be pronounced. Ali et al. (2009) developed a software tool to generate phonetic dictionaries for Arabic texts using Arabic pronunciation rules. , after modeling cross-word problem). The tool developed by Ali et al. (2009) takes care of some of within-word variations such as the context in which the words are uttered.

1007/978-1-4614-1213-7_3, # Dia AbuZeina 2012 25 26 3 The Baseline System represented in the transcription by either using a silence mark (Sukun or unvoweled) or dropping the vowel, which is considered equivalent to the silence mark. The transcription file contains 39,217 words. The vocabulary list contains 14,234 words. 21%. 1. We used Ryding (2005) as a reference. The short vowels Fatha, Damma, and Kasra are represented using a, u, and i, respectively. A phoneme is the basic unit of speech that is used in ASR systems.

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Cross-Word Modeling for Arabic Speech Recognition by Dia AbuZeina

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