Transliteration
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Transliteration is a mechanism for converting a word in a source (foreign) language to a target language, and often adopts approaches from machine translation. In machine translation, the objective is to preserve the semantic meaning of the utterance as much as possible while following the syntactic structure in the target language. In Transliteration, the objective is to preserve the original pronunciation of the source word as much as possible while following the phonological structures of the target language.
For example, the city’s name “Manchester” has become well known by people of languages other than English. These new words are often named entities that are important in cross-lingual information retrieval, information extraction, machine translation, and often present out-of-vocabulary challenges to spoken language technologies such as automatic speech recognition, spoken keyword search, and text-to-speech.
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Rethinking Hate Speech Detection on Social Media: Can LLMs Replace Traditional Models?
Beyond Specialization: Benchmarking LLMs for Transliteration of Indian Languages
Lost in Transliteration: Bridging the Script Gap in Neural IR
Bridging the Gap: An Intermediate Language for Enhanced and Cost-Effective Grapheme-to-Phoneme Conversion with Homographs with Multiple Pronunciations Disambiguation
Proper Name Diacritization for Arabic Wikipedia: A Benchmark Dataset
Low-Resource Transliteration for Roman-Urdu and Urdu Using Transformer-Based Models
ParsiPy: NLP Toolkit for Historical Persian Texts in Python
Connecting the Persian-speaking World through Transliteration
NusaAksara: A Multimodal and Multilingual Benchmark for Preserving Indonesian Indigenous Scripts
Linguistic Analysis of Sinhala YouTube Comments on Sinhala Music Videos: A Dataset Study
IndoNLP 2025: Shared Task on Real-Time Reverse Transliteration for Romanized Indo-Aryan languages
When LLMs Struggle: Reference-less Translation Evaluation for Low-resource Languages
Sinhala Transliteration: A Comparative Analysis Between Rule-based and Seq2Seq Approaches
LAMA-UT: Language Agnostic Multilingual ASR through Orthography Unification and Language-Specific Transliteration
Transliterated Zero-Shot Domain Adaptation for Automatic Speech Recognition
Romanized to Native Malayalam Script Transliteration Using an Encoder-Decoder Framework
PolyIPA -- Multilingual Phoneme-to-Grapheme Conversion Model
GR-NLP-TOOLKIT: An Open-Source NLP Toolkit for Modern Greek
AyutthayaAlpha: A Thai-Latin Script Transliteration Transformer
Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs
ChakmaNMT: A Low-resource Machine Translation On Chakma Language
UniGlyph: A Seven-Segment Script for Universal Language Representation
A two-stage transliteration approach to improve performance of a multilingual ASR
How Transliterations Improve Crosslingual Alignment
Exploring the Role of Transliteration in In-Context Learning for Low-resource Languages Written in Non-Latin Scripts
Can Small Language Models Learn, Unlearn, and Retain Noise Patterns?
Breaking the Script Barrier in Multilingual Pre-Trained Language Models with Transliteration-Based Post-Training Alignment
Jailbreaking LLMs with Arabic Transliteration and Arabizi
Review of Computational Epigraphy
TransMI: A Framework to Create Strong Baselines from Multilingual Pretrained Language Models for Transliterated Data
ParaNames 1.0: Creating an Entity Name Corpus for 400+ Languages using Wikidata
Swa Bhasha: Message-Based Singlish to Sinhala Transliteration
Charles Translator: A Machine Translation System between Ukrainian and Czech
Cost-Performance Optimization for Processing Low-Resource Language Tasks Using Commercial LLMs
Training a Bilingual Language Model by Mapping Tokens onto a Shared Character Space
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.