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

Keyphrases

• Arabic Dialect Identification 100%
• Arabic Dialects 50%
• ASR System 50%
• Bayes Neural Network 50%
• Bigram 50%
• Dialect Identification 50%
• Egyptian 50%
• F1 Score 50%
• Feature Combination 50%
• Feature Vector 50%
• Good Accuracy 50%
• High-score 50%
• Linear Kernel 100%
• Logistic Regression 50%
• Machine Learning Algorithms 50%
• Modern Standard Arabic 50%
• Naïve Bayes 50%
• Network Vector 50%
• North African 50%
• Overfitting 50%
• Small Data 50%
• Spoken Arabic 100%
• String Kernel 50%
• Support Vector Machine 100%
• Textual Features 100%
• Training Data 50%
• Trigram 50%

Computer Science

• Feature Vector 50%
• Logistic Regression 50%
• Machine Learning Algorithm 50%
• Neural Network 50%
• Support Vector Machine 100%
• Textual Feature 100%
• Training Data 50%

Mathematics

• Feature Vector 50%
• Logistic Regression 50%
• Naïve Bayes 50%
• Neural Network 50%
• Support Vector Machine 100%
• Training Data 50%