Method to Overcome the Ambiguities in Shallow Parse and Transfer Machine Translation
Year: 2018
Type: article
Abstract: The manuscript proposes a new architecture for a Shallow Parsing and Shallow Transfer Rule-Based Machine Translation System. The newly proposed architecture omits the disambiguation module in the starting phases of the translation pipeline and stores all translation candidates generated by the ambiguous process in the morphological analysis phase. The architecture is based on multigraphs. We propose a simplified version of k-best shortest path algorithm for this special case of directed multigraph. The k-best set is ranked using a trigram language model. The empirical evaluation shows that the new architecture produces better translation quality results with constant delay in time.
Source: Computing and Informatics
Authors: Jernej Vičič, Marko Grgurovič
Institution: University of Primorska
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2913194498