Skip to content

SinMix2Mono: A Dataset for Code-mixed Romanized Sinhala Translation and Transliteration

2026 · European Association for Machine Translation Conferences/Workshops · pp. 114-129 · 0 citations · 33 references
Computer Science

TL;DR

The largest manually annotated parallel training dataset, followed by the first gold standard benchmark and code-mixed transliteration ambiguity corpora for code-mixed romanized Sinhala to Sinhala conversion are introduced.

View source

Similar papers

Open access Sep 2026

A Translated Singlish SMS Dataset: Multi-Step LLM Language Detection and Translation for Code-Mixed Creole

Singlish is a code-mixed creole formed from English and multiple Asian languages and dialects, predominantly spoken in Singapore. Translation of Singlish to standard UK English broadens comprehension of the creole and supports downstream analyses such as sentiment analysis, yet few annotated resources exist for this pu...

L. H. X. Ng, Luo-Qi Chan · 0 citations
Open access 2026

AssamLegalTrans: A Parallel Corpus, Benchmark and Analysis for English-Assamese Machine Translation of Legal Judgments

This work introduces the first-of-its-kind English-Assamese parallel corpus for the translation of Indian court judgments and performs a comprehensive evaluation of state-of-the-art multilingual models in both zero-shot and fine-tuned settings, comparing their performance against commercial systems.

Telem Joyson Singh, Hemanta Baruah, Sanasam Ranbir Singh et al. · 1 citation
Open access 2026

Arabic ChartSumm: An English-to-Arabic Benchmark for Metadata-to-Text Summarization

Generating summaries from chart metadata in Arabic presents unique challenges at the intersection of cross-lingual transfer and data-to-text generation. Chart-to-text benchmarks have advanced English-language research, yet Arabic remains without a comparable resource, underscoring its continued underrepresentation in N...

Passant Elchafei, Amany Fashwan · 0 citations
Preprint Oct 2026

Benchmarking Large Language Models for Detecting Satirical Code-Mixed Sentences

Code-switching is a natural linguistic phenomenon, yet its impact on high-level reasoning tasks remains largely unexplored in under-resourced languages like Romanian. Natural language processing tasks, such as satire detection, rely heavily on nuanced cultural and syntactic cues that large language models struggle to c...

Răzvan-Alexandru Smădu, Ioana Buhnila, Daniela Tanase et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.