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Amazigh Grammatical Labelling using n-gram Properties and Segmentation Pre-treatment


 
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1. Title Title of document Amazigh Grammatical Labelling using n-gram Properties and Segmentation Pre-treatment
 
2. Creator Author's name, affiliation, country Mohamed Outahajala; EMI - IRCAM; Morocco
 
2. Creator Author's name, affiliation, country Yassine Benajiba; Philips Research North America; United States
 
2. Creator Author's name, affiliation, country Paolo Rosso; NLE Lab - DSIC, Technical University of Valencia; Spain
 
2. Creator Author's name, affiliation, country Lahbib Zenkouar; EMI, Mohammed V University - Agdal; Morocco
 
3. Subject Discipline(s)
 
3. Subject Keyword(s)
 
4. Description Abstract This paper present the first Amazigh POS tagger. Very few linguistic resources have been developed so far for Amazigh and we believe that the development of a POS tagger tool is the first step needed for automatic text processing. In order to achieve this endeavor, we have trained two sequence classification models using Support Vector Machines (SVMs) and Conditional Random Fields (CRFs) after using a tokenization step. We have used the 10-fold technique to evaluate our approach. Results show that the performance of SVMs and CRFs are very comparable. Across the board, SVMs outperformed CRFs on the fold level (92.58% vs. 92.14%) and CRFs outperformed SVMs on the 10 folds average level (89.48% vs. 89.29%). These results are very promising considering that we have used a corpus of only ~20k tokens.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2012-03-15
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF (Français (France))
 
10. Identifier Uniform Resource Identifier https://www.revue-eti.net/index.php/eti/article/view/60
 
11. Source Title; vol., no. (year) Electronic Journal of Information Technology; Issue 6
 
12. Language English=en fr
 
13. Relation Supp. Files
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
15. Rights Copyright and permissions Copyright (c) 2012 Mohamed Outahajala, Yassine Benajiba, Paolo Rosso, Lahbib Zenkouar
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.