The Arabic language is a collection of spoken dialects with important phonological, morphological, lexical, and syntactic differences, along with a standard written language, Modern Standard Arabic (MSA). Since the spoken dialects are not officially written, it is very costly to obtain adequate corpora to use for training dialect NLP tools such as parsers. In this paper, we address the problem of parsing transcribed spoken Levantine Arabic (LA). We do not assume the existence of any annotated LA corpus (except for development and testing), nor of a parallel corpus LA-MSA. Instead, we use explicit knowledge about the relation between LA and MSA
International audienceDialectal Arabic (DA) poses serious challenges for Natural Language Processing...
Research into statistical parsing for English has enjoyed over a decade of successful results. Howev...
This paper describes an Arabic dialect identification system which we developed for the Discriminati...
The Arabic language is a collection of spoken dialects with important phonological, morphological, l...
International audienceCreating parallel corpora is a difficult issue that many researches try to dea...
International audienceThe Algerian Arabic dialects are under-resourced languages, which lack both co...
This thesis discusses different approaches to machine translation (MT) from Dialectal Arabic (DA) to...
International audienceArabic dialects also called colloquial Arabic or vernaculars are spoken variet...
This thesis has two aims: developing resources for Arabic dialects and improving the speech recognit...
International audienceWe present, in this paper an Arabic multi-dialect study including dialects fro...
The Arabic language is a collection of multiple variants, among which Modern Standard Arabic (MSA) h...
International audienceThe developpment of NLP tools for dialects faces the severe problem of lack of...
International audienceThis research deals with Arabic dialect identification, a challenging issue re...
The term corpus comes from Latin and means “body”. According to corpus linguists, a corpus can be de...
We present in this paper PADIC, a Parallel Arabic DIalect Corpus we built from scratch, then we cond...
International audienceDialectal Arabic (DA) poses serious challenges for Natural Language Processing...
Research into statistical parsing for English has enjoyed over a decade of successful results. Howev...
This paper describes an Arabic dialect identification system which we developed for the Discriminati...
The Arabic language is a collection of spoken dialects with important phonological, morphological, l...
International audienceCreating parallel corpora is a difficult issue that many researches try to dea...
International audienceThe Algerian Arabic dialects are under-resourced languages, which lack both co...
This thesis discusses different approaches to machine translation (MT) from Dialectal Arabic (DA) to...
International audienceArabic dialects also called colloquial Arabic or vernaculars are spoken variet...
This thesis has two aims: developing resources for Arabic dialects and improving the speech recognit...
International audienceWe present, in this paper an Arabic multi-dialect study including dialects fro...
The Arabic language is a collection of multiple variants, among which Modern Standard Arabic (MSA) h...
International audienceThe developpment of NLP tools for dialects faces the severe problem of lack of...
International audienceThis research deals with Arabic dialect identification, a challenging issue re...
The term corpus comes from Latin and means “body”. According to corpus linguists, a corpus can be de...
We present in this paper PADIC, a Parallel Arabic DIalect Corpus we built from scratch, then we cond...
International audienceDialectal Arabic (DA) poses serious challenges for Natural Language Processing...
Research into statistical parsing for English has enjoyed over a decade of successful results. Howev...
This paper describes an Arabic dialect identification system which we developed for the Discriminati...