A Neural Network Based Model for Loanword Identification in Uyghur

Toward Better Loanword Identification in Uyghur Using Cross-lingual Word Embeddings

To enrich vocabulary of low resource settings, we proposed a novel method which identify loanwords in monolingual corpora. More specifically, we first use cross-lingual word embeddings as the core feature to generate sem…

Recurrent Neural Network Based Loanwords Identification in Uyghur

Are Language Models Borrowing-Blind? A Multilingual Evaluation of Loanword Identification across 10 Languages

Throughout language history, words are borrowed from one language to another and gradually become integrated into the recipient's lexicon. Speakers can often differentiate these loanwords from native vocabulary, particul…

Loanword or Switch? The Annotation Boundary, Not the Model, Drives Kazakh-Russian Code-Switching Identification

Off-the-shelf LID and letter heuristics over-label Kazakh-Russian social text as mixed: Russian loanwords inside Kazakh look like code-switching under a shared Cyrillic script. We release a document-level gold LID set wh…

Noisy Uyghur Text Normalization

Uyghur is the second largest and most actively used social media language in China. However, a non-negligible part of Uyghur text appearing in social media is unsystematically written with the Latin alphabet, and it cont…