Papers with Part-of-speech
Domain adaptation for part-of-speech tagging of noisy user-generated text (N19-1)
Copied to clipboard
| Challenge: | Existing POS taggers for canonical German text achieve good results around 97% accuracy, but when applying these trained models to out-of-domain data the performance decreases drastically. |
| Approach: | They propose a neural network that trains an out-of-domain model on a large newswire corpus and transfers those weights by using them as a prior for a model trained on the target domain. |
| Outcome: | The proposed model achieves a tagging accuracy of slightly over 90%, improving on the previous state of the art for this task. |
Part-of-Speech Tagging for Arabic Gulf Dialect Using Bi-LSTM (L18-1)
Copied to clipboard
| Challenge: | Part-of-speech (POS) tagging is one of the most important building blocks in many natural language processing (NLP) applications. |
| Approach: | They propose to use a POS tagger for Arabic Gulf dialect to improve POS tagging accuracy. |
| Outcome: | The proposed POS tagger improves POS tagging accuracy for the Arabic Gulf dialect from 75% accuracy to 91% accuracy using a bi-LSTM labeler. |