Computational linguistics and Natural Language Processing

Abstract

This chapter provides an introduction to computational linguistics methods, with focus on their applications to the practice and study of translation. It covers computational models, methods and tools for collection, storage, indexing and analysis of linguistic data in the context of translation, and discusses the main methodological issues and challenges in this field. While an exhaustive review of existing computational linguistics methods and tools is beyond the scope of this chapter, we describe the most representative approaches, and illustrate them with descriptions of typical applications.

This is the unedited author's copy of a text which appeared as a chapter in "The Routledge Handbook of Translation and Methodology'', edited by F Zanettin and C Rundle (2022)

References in corpus (2)

• Sequence to Sequence Learning with Neural Networks
• Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation