Papers by Andargachew Mekonnen Gezmu

2 papers
Extended Parallel Corpus for Amharic-English Machine Translation (2022.lrec-1)

Copied to clipboard

Challenge: Existing approaches to automate the complex task of translation are tedious and expensive.
Approach: They describe acquisition, preprocessing, segmentation, and alignment of an Amharic-English parallel corpus.
Outcome: The proposed corpus outperforms statistical machine translation models by six to seven BLEU points . the results show that the subword models outperformed word-based models by three to four BLUE points compared with the word-base models .
Portable Spelling Corrector for a Less-Resourced Language: Amharic (L18-1)

Copied to clipboard

Challenge: a corpus-driven spelling corrector for Amharic is ported to other languages with little effort . a term list is used for spelling errors and can handle rare terms, proper nouns and neologisms.
Approach: They propose an automatic spelling corrector for Amharic, the working language of the Federal Government of Ethiopia.
Outcome: The proposed method outperforms baseline systems in Amharic and English . it has smoothed language model, generalized error model and ability to take into account context of misspellings.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations