Summary of the paper
| Title | Automatic Identification of Arabic Dialects |
|---|---|
| Authors | Mohamed Belgacem, Georges Antoniadis and Laurent Besacier |
| Abstract | In this work, automatic recognition of Arabic dialects is proposed. An acousticsurvey of the proportion of vocalic intervals and the standard deviation ofconsonantal intervals in nine dialects (Tunisia, Morocco, Algeria, Egypt,Syria, Lebanon, Yemen, Golf’s Countries and Iraq) is performed using theplatform Alize and Gaussian Mixture Models (GMM). The results show thecomplexity of the automatic identification of Arabic dialects since. No clearborder can be found between the dialects, but a gradual transition betweenthem. They can even vary slightly from one city to another. The existence ofthis gradual change is easy to understand: it corresponds to a human and socialreality, to the contact, friendships forged and affinity in the environmentmore or less immediate of the individual. This document also raises questionsabout the classes or macro classes of Arabic dialects noticed from theconfusion matrix and the design of the hierarchical tree obtained. |
| Language | Sign Language Recognition/Generation |
| Topics | Speech resource/database, Language Identification, Sign Language Recognition/Generation |
Full paper  |
Automatic Identification of Arabic Dialects |
| Bibtex | @InProceedings{BELGACEM10.719, author = {Mohamed Belgacem, Georges Antoniadis and Laurent Besacier}, title = {Automatic Identification of Arabic Dialects}, booktitle = {Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Mike Rosner, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |