Name: ArVox
Description: designed for Multilingual and Arabic Dialect Identification
Provider: nan
Paper Title: A Language Identification System Based on Voxforge Speech Corpus
Tasks: dialect identification from speech 
Venue Name: International Conference on Advanced Machine Learning Technologies and Applications
Authors: Khaled Lounnas, Mourad Abbas, Hocine Teffahi, Mohamed Lichouri 
Abstract: In this work, we address the problem of identifying languages based on Voxforge speech corpus. We downloaded corpora for three languages: English, German and Persian from Voxforge. In addition, we recorded two additional corpora, the first one for Modern Standard Arabic (MSA) and the other one for Kabyl, one of the Algerian Berber dialects. To tackle this task, we used three classifiers, namely: k-Nearest Neighbors (kNN), Support Vector Machines (SVM) and Extra Trees Classifier. We obtained an average precision of 87.45% for binary classification compared to 44% for the multi-class one.