Papers by Chenggang Mi
Toward Better Loanword Identification in Uyghur Using Cross-lingual Word Embeddings (C18-1)
Copied to clipboard
| Challenge: | Almost every natural language processing task suffers from data sparseness. |
| Approach: | They propose a method which identify loanwords in monolingual corpora by using cross-lingual word embeddings as core feature and a log-linear model which combines several shallow features to predict the final results. |
| Outcome: | The proposed method outperforms baseline models significantly on loanword identification and translation in four languages and eight translation directions. |
Parallel sentences mining with transfer learning in an unsupervised setting (2021.naacl-srw)
Copied to clipboard
| Challenge: | Existing methods to mine parallel sentences in low-resource environments are not suitable for many low-level language pairs. |
| Approach: | They propose an approach based on transfer learning to mine parallel sentences in an unsupervised setting using bilingual corpora of low-resource language pairs. |
| Outcome: | The proposed model improves the performance of mined parallel sentences at two real-world low-resource language pairs compared with previous methods. |
A Neural Network Based Model for Loanword Identification in Uyghur (L18-1)
Copied to clipboard
| Challenge: | Lexical borrowing happens in almost all languages, and we propose a new method to identify loanwords in Uyghur. |
| Approach: | They propose a neural network based loanword identification model for Uyghur that captures past and future information and learns both word level and character level features automatically. |
| Outcome: | The proposed model outperforms baseline models on Chinese, Arabic and Russian loanword detection in Uyghur. |