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Natural Language Processing in Ethiopian Languages: Current State, Challenges, and Opportunities

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Natural Language Processing in Ethiopian Languages: Current State, Challenges, and Opportunities - arxiv

This survey delves into the current state of natural language processing (NLP) for four Ethiopian languages: Amharic, Afaan Oromo, Tigrinya, and Wolaytta. Through this paper, we identify key challenges and opportunities for NLP research in Ethiopia. Furthermore, we provide a centralized repository on GitHub that contains publicly available resources for various NLP tasks in these languages. This reposi tory can be updated periodically with contributions from other researchers. Our objective is to disseminate information to NLP researchers interested in Ethiopian languages and encourage future research in this domain.

1. NLP Tools

Tools Name Tools task Language support Resource link
amseg Segmenter, tokenizer, transliteration, romanization and normalization Amharic amseg
HornMorpho Morphological analysis Amhric, Afaan Ormo, Tigirgna HornMorpho
lemma Lemmatizer Amhric lemma

2. NLP Applications

2.1. Machine Translation (MT)

We discuss the MT progress for Ethiopian languages in three categories: English Centeric -> works done for the above target Ethiopian languages with English pair, Ethiopian - Ethiopian -> works done for Ethiopian language pairs without involving other languages and Multilingual MT -> works done for Ethiopian languages with other languages in a multilingual setting.

2.1.1 English centeric

2.1.2 Local to Local

2.1.3 Multilingual

2.2. POS Tagging

2.3. Question Classification and Answering

2.4. Named Entity Recognition (NER)

2.5. Text Classification

2.5.1 Hate Speech Detection

2.5.2 Sentiment Analysis

2.5..3 News Classification

2.5.4. Text Summarization