Morphological Disambiguation Of Tunisian Dialect
| المصدر: | مجلة جامعة الملك سعود - علوم الحاسب والمعلومات |
|---|---|
| الناشر: | جامعة الملك سعود |
| المؤلف الرئيسي: | Zribi, Ines (Author) |
| مؤلفين آخرين: | Ellouze, Mariem (Co-Author), Belguith, Lamia Hadrich (Co-Author), Blache, Philippe (Co-Author) |
| المجلد/العدد: | مج29, ع2 |
| محكمة: | نعم |
| الدولة: |
السعودية |
| التاريخ الميلادي: |
2017
|
| الصفحات: | 147 - 155 |
| DOI: |
10.33948/0584-029-002-002 |
| ISSN: |
1319-1578 |
| رقم MD: | 974083 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | science |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Tunisian Dialect | Spoken Language | Morphological Analysis | Morphological Disambiguation
|
| رابط المحتوى: |
| المستخلص: |
In this paper, we propose a method to disambiguate the output of a morphological analyzer of the Tunisian dialect. We test three machine learning techniques that classify the morphological analysis of each word token into two classes: true and false. The class label is assigned to each analysis according to the context of the corresponding word in a sentence. In failure cases, we combine the results of the proposed techniques with a bigram classifier to choose only one analysis for a given word. We disambiguate the result of the morphological analyzer of the Tunisian Dialect Al-Khalil-TUN (Zribi et al., 2013b). We use the Spoken Tunisian Arabic Corpus STAC (Zribi et al., 2015) to train and test our method. The evaluation shows that the proposed method has achieved an accuracy performance of 87.32%. |
|---|---|
| ISSN: |
1319-1578 |
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