Transliteration Characteristics in Romanized Assamese Language Social Media Text and Machine Transliteration

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AKJY9TPZP" target="_blank" >RIV/00216208:11320/25:KJY9TPZP - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186192401&doi=10.1145%2f3639565&partnerID=40&md5=05c10fd5f07edc9da61c4a1148eb97c1" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186192401&doi=10.1145%2f3639565&partnerID=40&md5=05c10fd5f07edc9da61c4a1148eb97c1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3639565" target="_blank" >10.1145/3639565</a>

Result language

angličtina

Original language name

Transliteration Characteristics in Romanized Assamese Language Social Media Text and Machine Transliteration

Original language description

This article aims to understand different transliteration behaviors of Romanized Assamese text on social media. Assamese, a language that belongs to the Indo-Aryan language family, is also among the 22 scheduled languages in India. With the increasing popularity of social media in India and also the common use of the English Qwerty keyboard, Indian users on social media express themselves in their native languages, but using the Roman/Latin script. Unlike some other popular South Asian languages (say Pinyin for Chinese), Indian languages do not have a common standard romanization convention for writing on social media platforms. Assamese and English are two very different orthographical languages. Thus, considering both orthographic and phonemic characteristics of the language, this study tries to explain how Assamese vowels, vowel diacritics, and consonants are represented in Roman transliterated form. From a dataset of romanized Assamese social media texts collected from three popular social media sites: (Facebook, YouTube, and X (formerly known as Twitter)),1 we have manually labeled them with their native Assamese script. A comparison analysis is also carried out between the transliterated Assamese social media texts with six different Assamese romanization schemes that reflect how Assamese users on social media do not adhere to any fixed romanization scheme. We have built three separate character-level transliteration models from our dataset. One using a traditional phrase-based statistical machine transliteration model, (1) PBSMT model and two separate neural transliteration models, (2) BiLSTM neural seq2seq model with attention, and (3) Neural transformer model. A thorough error analysis has been performed on the transliteration result obtained from the three state-of-the-art models mentioned above. This may help to build a more robust machine transliteration system for the Assamese social media domain in the future. Finally, an attention analysis experiment is also carried out with the help of attention weight scores taken from the character-level BiLSTM neural seq2seq transliteration model built from our dataset. © 2024 Association for Computing Machinery. All rights reserved.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

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

Project

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Continuities

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Publication year

2024

Confidentiality

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

Name of the periodical

ACM Transactions on Asian and Low-Resource Language Information Processing

ISSN

2375-4699

e-ISSN

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Volume of the periodical

23

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

36

Pages from-to

1-36

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85186192401