Machine translation

Mục tiêu nghiên cứu của luận văn là vận dụng kiến thức đã học để xây dựng một hệ thống trả lời tự động, sử dụng mạng học sâu Deep Neural Networks, dựa trên khung làm việc sequence-to-sequence và cơ chế attention để sinh ra câu trả lời tự động từ một chuỗi đầu vào tương ứng. Mô hình được huấn luyện end-to-end GNMT (Google’s Neural Machine Translation) trên tập dữ liệu miền mở có sẵn.

72p matroinho2510 08-11-2022 57 17   Download

The purpose of this thesis is to propose two models for using cross-lingual word embedding models to address the above impediment. The first model enhances the quality of the phrase-table in SMT, and the remaining model tackles the unknown word problem in NMT.

14p tamynhan0 04-07-2020 27 3   Download

The purpose of this thesis is to propose two models for using cross-lingual word embedding models to address the above impediment. The first model enhances the quality of the phrase-table in SMT, and the remaining model tackles the unknown word problem in NMT.

54p tamynhan0 04-07-2020 16 5   Download

Lecture “Natural language processing – Chapter 5: Foundation of statistical machine translation” has contents: Introduction to statistical machine translation, statistical MT systems, three problems in statistical MT systems, translation model, and other contents.

12p dien_vi01 21-11-2018 23 1   Download

In the past, we presented tutorials called “Introduction to Statistical Machine Translation”, aimed at people who know little or nothing about the field and want to get acquainted with the basic concepts. This tutorial, by contrast, goes more deeply into selected topics of intense current interest. We aim at two types of participants: 1. People who understand the basic idea of statistical machine translation and want to get a survey of hot-topic current research, in terms that they can understand. 2.

1p hongphan_1 15-04-2013 64 3   Download

Semantic Role Labeling (SRL) consists of, given a sentence, detecting basic event structures such as “who” did “what” to “whom”, “when” and “where”. From a linguistic point of view, a key component of the task corresponds to identifying the semantic arguments filling the roles of the sentence predicates. Typical predicate semantic arguments include Agent, Patient, and Instrument, but semantic roles may also be found as adjuncts (e.g., Locative, Temporal, Manner, and Cause).

1p hongphan_1 15-04-2013 55 2   Download

We describe Joshua (Li et al., 2009a)1 , an open source toolkit for statistical machine translation. Joshua implements all of the algorithms required for translation via synchronous context free grammars (SCFGs): chart-parsing, n-gram language model integration, beam- and cubepruning, and k-best extraction. The toolkit also implements suffix-array grammar extraction and minimum error rate training. It uses parallel and distributed computing techniques for scalability.

4p hongphan_1 15-04-2013 48 2   Download

We developed caitra, a novel tool that aids human translators by (a) making suggestions for sentence completion in an interactive machine translation setting, (b) providing alternative word and phrase translations, and (c) allowing them to postedit machine translation output. The tool uses the Moses decoder, is implemented in Ruby on Rails and C++ and delivered over the web. We are at the beginning of a research program to explore the benefits of these different types of aid to human translators, analyze user interaction behavior, and develop novel types of assistance. ...

4p hongphan_1 15-04-2013 66 2   Download