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2016 COLING COLING 2016

YAMAMA: Yet Another Multi-Dialect Arabic Morphological Analyzer

Abstract

AbstractIn this paper, we present YAMAMA, a multi-dialect Arabic morphological analyzer and disambiguator. Our system is almost five times faster than the state-of-art MADAMIRA system with a slightly lower quality. In addition to speed, YAMAMA outputs a rich representation which allows for a wider spectrum of use. In this regard, YAMAMA transcends other systems, such as FARASA, which is faster but provides specific outputs catering to specific applications.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning
🧭 Keyword Pioneer — arabic nlp
🐣 Hot Topic Early Bird — part-of-speech tagging
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Security & Privacy, Speech & Audio

Authors

Salam Khalifa , Nasser Zalmout , Nizar Habash

Topics

Artificial Intelligence > Learning Paradigms > Transfer Learning Machine Learning > Core Methods > Classification

Keywords

part-of-speech tagging morphological analysis arabic language arabic nlp morphological disambiguation text processing
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