QCRI Arabic Dialects Identification (QADI) Corpus

Domaine:

natural language processing

Type de record:

dataset

QCRI Arabic Dialects Identification (QADI) is a Country-level Arabic dialects identification (DI) dataset. It provides a collection for benchmarking DI task.The dataset contains 540,590 tweets from 18 Arab countries.

QCRI @ DSL 2016: Spoken Arabic Dialect Identification Using Textual Features

The paper describes the QCRI submissions to the task of automatic Arabic dialect classification into 5 Arabic variants, namely Egyptian, Gulf, Levantine, North-African, and Modern Standard Arabic (MSA). The training data is relatively small and is automatically gen

MIT-QCRI Arabic Dialect Identification System for the 2017 Multi-Genre Broadcast Challenge

In order to successfully annotate the Arabic speech con- tent found in open-domain media broadcasts,

The identification of two Algerian Arabic dialects by prosodic focus

The purpose of this research is to show that it is easier to identify the prosody of Algiers and Ora

OMAN-SPEECH: A Multi-Layer Annotated Speech Corpus for Omani Arabic Dialects

Automatic Speech Recognition (ASR) has achieved strong performance in high-resource languages; howev

drelhaj/Arabic-Dialects

The Arabic Dialects Dataset is a specialised corpus designed for automatic dialect identification, w

AN IDENTIFICATION MODEL USED FOR ARABIC LIBYAN DIALECTS BASED ON MACHINE LEARNING APPROACH

In this research work we have especially studied both Modern Standard Arabic Language and Libyan Dia

QCRI Arabic Dialects Identification (QADI) Corpus

Domaine:

Type de record:

Visit

Connected records

Tasks

Languages