Robust Part of Speech Tagging
Generally, NLP tools use well-formed and annotated data to learn patterns by using machine learning techniques. However, in this work we will focus on the language used in an on-line platform for machine translation. In this area it is usual to have a framework such the following: a web-page which o...
| Author: | |
|---|---|
| Format: | master thesis |
| Publication Date: | 2013 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2099.1/17174 |
| Online Access: | https://hdl.handle.net/2099.1/17174 |
| Access Level: | Open access |
| Keyword: | Machine translating Natural language processing (Computer science) Traducció automàtica Tractament del llenguatge natural (Informàtica) Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural |
| Summary: | Generally, NLP tools use well-formed and annotated data to learn patterns by using machine learning techniques. However, in this work we will focus on the language used in an on-line platform for machine translation. In this area it is usual to have a framework such the following: a web-page which offer a service of translation between pairs of languages. The problem is that the casual users utilize the service to translate any type of text (cut and paste, single words, bad formatting, snipets, informal language, pre-traductions, etc.). Hence, in this situation we will find very often words with mistakes that make the system provides a bad translation because it is not able to understand the input. |
|---|