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Dialect Identification

Dialectal Arabic Identification

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Showing 126–150 of 189 papers

TitleStatusHype
ST MADAR 2019 Shared Task: Arabic Fine-Grained Dialect Identification—0
STT4SG-350: A Speech Corpus for All Swiss German Dialect Regions—0
T\"ubingen-Oslo Team at the VarDial 2018 Evaluation Campaign: An Analysis of N-gram Features in Language Variety Identification—0
Team JUST at the MADAR Shared Task on Arabic Fine-Grained Dialect Identification—0
Text and Speech-based Tunisian Arabic Sub-Dialects Identification—0
The MADAR Shared Task on Arabic Fine-Grained Dialect Identification—0
The QMUL/HRBDT contribution to the NADI Arabic Dialect Identification Shared Task—0
The SMarT Classifier for Arabic Fine-Grained Dialect Identification—0
Towards spoken dialect identification of Irish—0
Towards Zero-Shot Text-To-Speech for Arabic Dialects—0
Transfer Learning Improves French Cross-Domain Dialect Identification: NRC @ VarDial 2022—0
TunBERT: Pretrained Contextualized Text Representation for Tunisian Dialect—0
Twist Bytes - German Dialect Identification with Data Mining Optimization—0
TwistBytes - Identification of Cuneiform Languages and German Dialects at VarDial 2019—0
UL2C: Mapping User Locations to Countries on Arabic Twitter—0
UnibucKernel: An Approach for Arabic Dialect Identification Based on Multiple String Kernels—0
UnibucKernel: Geolocating Swiss German Jodels Using Ensemble Learning—0
UnibucKernel Reloaded: First Place in Arabic Dialect Identification for the Second Year in a Row—0
Unsupervised Deep Language and Dialect Identification for Short Texts—0
Unsupervised Out-of-Distribution Dialect Detection with Mahalanobis Distance—0
Unsupervised Representation Learning of Speech for Dialect Identification—0
USTHB at NADI 2023 shared task: Exploring Preprocessing and Feature Engineering Strategies for Arabic Dialect Identification—0
Verifiably Effective Arabic Dialect Identification—0
Voice Conversion Improves Cross-Domain Robustness for Spoken Arabic Dialect Identification—0
Vowel-based Meeteilon dialect identification using a Random Forest classifier—0
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