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[9001053.] رقم البحث : 9001053 - |
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Building a POS-Annotated Corpus for Egyptian Children / |
| تخصص البحث : Large Corpora |
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هندسة اللغة: |
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Heba Salama ( Heba.salama.slp@gmail.com - ) - مؤلف رئيسي |
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Sameh Alansary ( Sameh.Alansary@bibalex.org - ) |
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POS annotated corpus, CHILDES database |
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In this paper, we present an attempt at developing a POS annotated corpus for Egyptian children.Linguistic annotation of the corpora provides researchers with better means for exploring the development of grammatical constructions and their usage.This is an initial annotated corpus for Egyptian children. It implements part of speech tag (POS) especially a morphologically annotated corpus of spoken Arabic child language.POS are made in ”%mor” ’morphology’ tiers manually. Coding language transcripts for computer analysis is a daunting task. It approximately took 170 hours, and thus manual annotation focused on a particular child.The POS coding process started with a purely manually annotation of 2701words. 1380 words annotated for an adultand 1321 annotated words for the child was handled. Annotated child language proved to be challenging, and time consuming task.The MOR grammar exists in many languages, such as English, French, German, Japanese, Cantonese, Hebrew, and they are generated automatically, the CLAN has the automatic coding system ”MOR program”. In Egyptian Arabic, this is not applied for two reasons. First, there is no previous Egyptian Arabic work done on a constructing system for such a representation. Second, morphology of Egyptian Arabic is very rich and different from other languages. Thus, their rules cannot be applied to Arabic. In the two Arabic studies of Qatari and Emirati languages, semi-automatic and mini automatic MOR is used.Finally,certain applications of linguistic analysis commands are provided by using CLAN software. The analyses include frequency counts, word searches, co-occurrence analyses; MLU (mean length of utterance) counts and analyzes specified pairs of utterances. Transcript data provide some morphological analysis, such as mean length of utterance (MLU) counts, lexical analysis, such as frequency (FREQ) count, syntactic analysis, such as searching the data for specified combinations of words or complex string patterns (COMBO) count, as well as the discourse and interactional analysis, such as analyzes specified pairs of utterances (CHIP) count. |
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