International audienceWe present, in this paper an Arabic multi-dialect study including dialects from both the Maghreb and the Middle-east that we compare to the Modern Standard Arabic (MSA). Three dialects from Maghreb are concerned by this study: two from Algeria and one from Tunisia and two dialects from Middle-east (Syria and Palestine). The resources which have been built from scratch have lead to a collection of a multi-dialect parallel resource. Furthermore, this collection has been aligned by hand with a MSA corpus. We conducted several analytical studies in order to understand the relationship between these vernacular languages. For this, we studied the closeness between all the pairs of dialects and MSA in terms of Hellinger dista...
International audiencePADIC is a multidialectal parallel Arabic corpus. It was composed initially by...
International audienceThe development of natural language processing tools for dialects faces the se...
International audienceNeural Machine Translation (NMT) systems have been shown to perform impressive...
We present in this paper PADIC, a Parallel Arabic DIalect Corpus we built from scratch, then we cond...
International audienceCreating parallel corpora is a difficult issue that many researches try to dea...
International audienceArabic dialects also called colloquial Arabic or vernaculars are spoken variet...
International audienceThis research deals with Arabic dialect identification, a challenging issue re...
International audienceThe Algerian Arabic dialects are under-resourced languages, which lack both co...
International audienceThis paper presents a linguistic study of an algerian arabic dialect, namely t...
The daily spoken variety of Arabic is often termed the colloquial or dialect form of Arabic. There a...
International audienceNatural Language Processing for Arabic dialects has grown widely these last ye...
We present a study on sentence-level Arabic Dialect Identification using the newly developed Multidi...
This research is divided into two interlinked parts. The first part reviews literature on the diglos...
Automatic language processing is based on the use of language resources such as corpora, dictionarie...
The Arabic language is a collection of spoken dialects with important phonological, morphological, l...
International audiencePADIC is a multidialectal parallel Arabic corpus. It was composed initially by...
International audienceThe development of natural language processing tools for dialects faces the se...
International audienceNeural Machine Translation (NMT) systems have been shown to perform impressive...
We present in this paper PADIC, a Parallel Arabic DIalect Corpus we built from scratch, then we cond...
International audienceCreating parallel corpora is a difficult issue that many researches try to dea...
International audienceArabic dialects also called colloquial Arabic or vernaculars are spoken variet...
International audienceThis research deals with Arabic dialect identification, a challenging issue re...
International audienceThe Algerian Arabic dialects are under-resourced languages, which lack both co...
International audienceThis paper presents a linguistic study of an algerian arabic dialect, namely t...
The daily spoken variety of Arabic is often termed the colloquial or dialect form of Arabic. There a...
International audienceNatural Language Processing for Arabic dialects has grown widely these last ye...
We present a study on sentence-level Arabic Dialect Identification using the newly developed Multidi...
This research is divided into two interlinked parts. The first part reviews literature on the diglos...
Automatic language processing is based on the use of language resources such as corpora, dictionarie...
The Arabic language is a collection of spoken dialects with important phonological, morphological, l...
International audiencePADIC is a multidialectal parallel Arabic corpus. It was composed initially by...
International audienceThe development of natural language processing tools for dialects faces the se...
International audienceNeural Machine Translation (NMT) systems have been shown to perform impressive...