Challenge: MY-AKKHARA is a method used to input Burmese texts encoded in the Unicode standard, based on commonly accepted Latin transcription.
Approach: They propose a method to input Burmese texts encoded in the Unicode standard based on 26 lowercase Latin letters and 26 uppercase Latin keys as shortcuts for lowercase letters.
Outcome: The proposed method can input arbitrary Burmese strings with 26 lowercase Latin letters and 26 uppercase Latin characters on a QWERTY keyboard.

Similar Papers

Burmese Speech Corpus, Finite-State Text Normalization and Pronunciation Grammars with an Application to Text-to-Speech (2020.lrec-1)

Copied to clipboard

Challenge: Using crowd-sourced speech corpus and finite-state transducer grammars, we build a text-to-speech system for Burmese, a tonal Southeast Asian language from the Sino-Tibetan family.
Approach: They propose an open-source crowd-sourced multi-speaker speech corpus and finite-state grammars for performing grapheme-to-phoneme conversion for Burmese.
Outcome: The proposed system performs well for Burmese in a low-resource setting.
A Myanmar (Burmese)-English Named Entity Transliteration Dictionary (2020.lrec-1)

Copied to clipboard

Challenge: Currently, there are no data available for the transcription of borrowed English words in Myanmar . lack of resources is a problem for many understudied languages .
Approach: They construct a dictionary of Myanmar-English transliteration instances using a CC BY-NC-SA license.
Outcome: The proposed model outperforms the statistical model significantly on the character level.
Simplified Abugidas (P18-2)

Copied to clipboard

Challenge: Abugidas are writing systems where consonant letters represent syllables with a default vowel and other vowels are denoted by diacritics.
Approach: They investigated the feasibility of recovering the original text written in an abugida after omitting subordinate diacritics and merging consonant letters with similar phonetic values.
Outcome: The proposed method recovers the original text written in an abugida with 94% - 97% accuracy at the top-1 level and 98% - 99% at the bottom-4 level even after omitting most diacritics and merging the remaining 30 - 50 characters into 21 graphemes.
myMediCon: End-to-End Burmese Automatic Speech Recognition for Medical Conversations (2024.lrec-main)

Copied to clipboard

Challenge: Existing medical conversation speech corpora for Burmese are limited, despite advances in ASR.
Approach: They propose to use a manually curated medical conversation speech corpus for Burmese to examine the performance of ASR models.
Outcome: The proposed model outperforms the Transformer model and the Recurrent Neural Network (RNN) models.
Criteria for Useful Automatic Romanization in South Asian Languages (2022.lrec-1)

Copied to clipboard

Challenge: a number of possible criteria for systems that transliterate South Asian languages are considered . romanization is the special case where the target script is the Latin script.
Approach: They propose a set of criteria for systems that transliterate South Asian languages . criteria include fidelity to human linguistic behavior, processing utility for people, invertibility . they then propose several algorithms that address different criteria .
Outcome: The proposed algorithms address linguistic considerations in the context of Brahmic scripts and languages that use them, such as Hindi and Malayalam.
Out-of-the-box Universal Romanization Tool uroman (P18-4)

Copied to clipboard

Challenge: uroman converts text in Chinese, Arabic and Cyrillic into a common Latin-script representation . the tool uses string similarity metrics to compare text from different scripts .
Approach: They propose a tool that converts text in Chinese, Arabic and Cyrillic into a common Latin-script representation.
Outcome: uroman converts text in Chinese, Arabic and Cyrillic into a common Latin-script representation . the tool is available as a Perl script and as an interactive demo web page .
Corpus-Dependent Subcharacter Encoding via HMM-Guided Code Assignment (2026.acl-long)

Copied to clipboard

Challenge: Latom is a corpus-dependent alternative to byte encoding that learns fixed-length atomic codes from text.
Approach: They propose a corpus-dependent alternative to byte encoding that learns fixed-length atomic codes from text.
Outcome: The proposed framework improves text classification accuracy and reduces decoding errors.
Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset (2020.lrec-1)

Copied to clipboard

Challenge: a new resource is available for 12 South Asian languages that use the Latin script for text entry . the Latin-script system is not widely used in South Asian language writing, despite the Latin alphabet .
Approach: They describe the Dakshina dataset, a new resource consisting of text in both the Latin and native scripts for 12 South Asian languages.
Outcome: The Dakshina dataset includes text in both the Latin and native scripts for 12 languages . the authors provide baseline results on several tasks made possible by the dataset .
Finite-state script normalization and processing utilities: The Nisaba Brahmic library (2021.eacl-demos)

Copied to clipboard

Challenge: a library for low-level processing of brahmic scripts is available for free.
Approach: They propose an open-source library for efficient low-level processing of ten major South Asian Brahmic scripts.
Outcome: The proposed library supports low-level processing of ten major south Asian Brahmic scripts.
ViGPTQA - State-of-the-Art LLMs for Vietnamese Question Answering: System Overview, Core Models Training, and Evaluations (2023.emnlp-industry)

Copied to clipboard

Challenge: Large language models (LLMs) and their applications in low-resource languages are limited due to lack of training data and benchmarking datasets.
Approach: They propose a question-response system for Vietnamese that uses LLMs . they propose to open-source the model and train it on benchmark datasets based on Vietnamese data .
Outcome: The proposed question answering system for Vietnamese is open-source and performant . it can learn and capture human-like text, but there is a gap in evaluations for Vietnamese .

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