CALYOU
A Comparable Spoken Algerian Corpus Harvested from YouTube
Multiple Institutions 
CALYOU: A Comparable Spoken Algerian Corpus Harvested from YouTube

machine translation
Conference of the International Speech Communication Association
K. Abidi,M. Menacer,Kamel Smaïli
This paper addresses the issue of comparability of comments 
 extracted from Youtube. The comments concern spoken 
 Algerian which could be either local Arabic, Modern Standard 
 Arabic or French. This diversity of expression arises a huge 
 number of problems concerning the data processing. In this 
 article, several methods of alignment will be proposed and 
 tested. The method which permits to best align is Word2Vec-based 
 approach that will be used iteratively. This recurrent 
 call of Word2Vec allows to improve significantly the results 
 of comparability. In fact, a dictionary-based approach leads 
 to a Recall of 4, while our approach allows to get a Recall of 
 33 at rank 1. Thanks to this approach, we built from Youtube 
 CALYOU, a Comparable Corpus of the spoken Algerian.