Birhanie, Worku and Butt, Miriam (2020) Automatic Amharic Part of Speech Tagging (AAPOST): A Comparative Approach Using Bidirectional LSTM and Conditional Random Fields (CRF) Methods. In: Advances of Science and Technology. 7th EAI International Conference, ICAST 2019, Bahir Dar, Ethiopia, August 2–4, 2019, Proceedings.
![[thumbnail of 38922.pdf]](http://eprints.eai.eu/style/images/fileicons/application_pdf.png "38922.pdf")
PDF
38922.pdf
Download (890kB)
Abstract
Part of speech (POS) tagging is an initial task for many natural language applications. POS tagging for Amharic is in its infancy. This study contributes towards the improvement of Amharic POS tagging by experimenting using Deep Learning and Conditional Random Fields (CRF) approaches. Word embedding
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 13:19 |
| Last Modified: | 17 Apr 2026 11:08 |
| URI: | http://eprints.eai.eu/id/eprint/29215 |
Actions (login required)
- View Item