Automatic Speech Recognition (ASR), also known as Speech-To-Text (STT) or computer
speech recognition, has been an active field of research recently. This study aims to chart …

Natural Language Processing for Arabic dialects has grown widely these last years. Indeed,
several works were proposed dealing with all aspects of Natural Language Processing …

This paper presents Nabra, a corpora of Syrian Arabic dialects with morphological
annotations. A team of Syrian natives collected more than 6K sentences containing about …

The processing of the Arabic language is a complex field of research. This is due to many
factors, including the complex and rich morphology of Arabic, its high degree of ambiguity …

Comparing Arabic to other languages, Arabic lacks large corpora for Natural Language
Processing (Assiri, Emam & Al-Dossari, 2018; Gamal et al., 2019). A number of scholars …

We present an ongoing effort on the first large-scale morphologically manually annotated
corpus of Emirati Arabic. This corpus includes about 200,000 words selected from eight …

In this paper, we propose a method to disambiguate the output of a morphological analyzer
of the Tunisian dialect. We test three machine-learning techniques that classify the …

This paper provides a structured examination of Arabic Automatic Speech Recognition
(ASR), focusing on the complexity posed by the language's diverse forms and dialectal …

Recognize automatically the spontaneous Human speech and transcribe it into text is
becoming an important task. However, freely available models are rare especially for under …

The wide usage of multiple spoken Arabic dialects on social networking sites stimulates
increasing interest in Natural Language Processing (NLP) for dialectal Arabic (DA). Arabic …