Corpus Generation to Develop Amharic Morphological Segmenter

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AXIX2EJI7" target="_blank" >RIV/00216208:11320/23:XIX2EJI7 - isvavai.cz</a>

Result on the web

<a href="https://www.proquest.com/docview/2883174197/abstract/B90879C438B4510PQ/1" target="_blank" >https://www.proquest.com/docview/2883174197/abstract/B90879C438B4510PQ/1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14569/IJACSA.2023.01409116" target="_blank" >10.14569/IJACSA.2023.01409116</a>

Result language

angličtina

Original language name

Corpus Generation to Develop Amharic Morphological Segmenter

Original language description

"Morphological segmenter is an important component in Amharic natural language processing systems. Despite this fact, Amharic lacks large amount of morphologically segmented corpus. Large amount of corpus is often a requirement to develop neural network-based language technologies. This paper presents an alternative method to generate large amount of morph-segmented corpus for Amharic language. First, a relatively small (138,400 words) morphologically annotated Amharic seed-corpus is manually prepared. The annotation enables to identify prefixes, stem, and suffixes of a given word. Second, a supervised approach is used to create a conditional random field-based seed-model (on the seed-corpus). Applying the seed-model (an unsupervised technique on a large unsegmented raw Amharic words) for prediction, a large corpus size (3,777,283) of segmented words are automatically generated. Third, the newly generated corpus is used to train an Amharic morphological segmenter (based on a supervised neural sequence-to-sequence (seq2seq) approach using character embeddings). Using the seq2seq method, an F-score of 98.65% was measured. Results show an agreement with previous efforts for Arabic language. The work presented here has profound implications for future studies of Ethiopian language technologies and may one day help solve the problem of the digital-divide between resource-rich and under-resourced languages."

Czech name

—

Czech description

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Type

J_ost - Miscellaneous article in a specialist periodical

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

—

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

"International Journal of Advanced Computer Science and Applications"

ISSN

2158107X

e-ISSN

—

Volume of the periodical

14

Issue of the periodical within the volume

9

Country of publishing house

US - UNITED STATES

Number of pages

9

Pages from-to

1114 - 1122

UT code for WoS article

001084849700001

EID of the result in the Scopus database

2-s2.0-85173165158