Contrast Preservation in dialects of North Levantine Arabic
نویسندگان
چکیده
منابع مشابه
Machine Translation of Arabic Dialects
Arabic Dialects present many challenges for machine translation, not least of which is the lack of data resources. We use crowdsourcing to cheaply and quickly build LevantineEnglish and Egyptian-English parallel corpora, consisting of 1.1M words and 380k words, respectively. The dialectal sentences are selected from a large corpus of Arabic web text, and translated using Amazon’s Mechanical Tur...
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In this work, automatic recognition of Arabic dialects is proposed. An acoustic survey of the proportion of vocalic intervals and the standard deviation of consonantal intervals in nine dialects (Tunisia, Morocco, Algeria, Egypt, Syria, Lebanon, Yemen, Golf’s Countries and Iraq) is performed using the platform Alize and Gaussian Mixture Models (GMM). The results show the complexity of the autom...
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The Arabic language is a collection of spoken dialects with important phonological, morphological, lexical, and syntactic differences, along with a standard written language, Modern Standard Arabic (MSA). Since the spoken dialects are not officially written, it is very costly to obtain adequate corpora to use for training dialect NLP tools such as parsers. In this paper, we address the problem ...
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A comparison of F0 alignment values was carried out for three Arabic dialects (Moroccan Arabic, Kuwaiti Arabic and Yemeni Arabic) using five speakers from each dialect. Clear differences found in alignment enable separation of Moroccan Arabic from the two other dialects: a) values of the F0 valley differed significantly, with Moroccan Arabic showing a later synchronisation than Kuwaiti Arabic a...
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The Arabic language is characterized by the existence of many different colloquial varieties that significantly differ from the standard Arabic form. In this paper, we propose a state-of-the-art speech recognition system for Levantine Colloquial Arabic (LCA). A fully continuous context dependent acoustic model was trained using 50 hours of speech from the BBN DARPA Babylon corpus. Pronunciation...
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ژورنال
عنوان ژورنال: LSA Annual Meeting Extended Abstracts
سال: 2010
ISSN: 2377-3367
DOI: 10.3765/exabs.v0i0.489