Interactive machine translation pdf

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An interactive beam search visualization and graph visualization for attention weights can be used for post-editing and understanding machine-generated translations. The machine translation model is updated from user corrections to improve the translation quality of the whole document. We designed our approach for an LSTM-based translation model
PDF – Automatic machine translation is super efficient to produce translations yet their quality is not guaranteed This technique report introduces TranSmart, a practical human-machine interactive translation system that is able to trade off translation quality and efficiency Compared to existing publicly available interactive translation systems, TranSmart supports three key features, word
We study the application of active learning techniques to the translation of unbounded data streams via interactive neural machine translation. The main idea is to select, from an unbounded stream of source sentences, those worth to be supervised by a human agent. The user will interactively translate those samples.
Machine Translation Interactive machine translation HQT: Human-machine interaction (HMI) In classical MT and CAT, the interaction between human translators and machines is very limited. At the origin: HMI focused on disambiguation of the source text or for updating user dictionaries or for searching through dictionaries [Slocum, CL 1985][Whitelock et al., COLING 1986]. In the industry: simple
3 A Hybrid Approach to Interactive Machine-Aided Translation This section describes the model and the algorithm of the proposed method. First, the basic model of step­ wise bottom-up interactive translation is described in the subsection 3.1. Then the next subsection describes how different translation paradigms can be integrated in this model A Hybrid Machine Translation Framework for an Improved Translation Workflow Dissertation zur Erlangung des akademischen Grades eines Doktors der Philosophie der Philosophischen Fakultäten der Universität des Saarlandes vorgelegtvon Santanu Pal aus Sonamukhi, West Bengal, Indien Saarbrücken, 2018. DerDekan: Prof. Dr. RolandMarti Erstberichterstatter: Prof. Dr. JosefvanGenabith
this article points out the specific characteristics of interactive machine translation implemented in toptrans (controlled language, interactive disambiguation, terminology support, stylistic selection etc.), describes the supporting software (translation memories, text filter and editor) and gives a summary of experiences in practical use with …
In interactive machine translation (MT), human translators correct errors in automatic translations in collaboration with the MT systems, and this is an effective way to improve productivity gain in translation. Phrase-based statistical MT (PB-SMT) has been the mainstream approach to MT for the past 30 years, both in academia and industry. Neural MT (NMT), an end-to-end learning approach to MT
In this work, we propose different active learning tech- niques for interactive machine translation. Results show that for a given translation quality the use of active learning allows us to greatly reduce the human effort required to translate the sentences in the stream. 1 Introduction
Request PDF | Interactive machine translation using hierarchical translation models | Current automatic machine translation systems are not able to generate error-free translations and human
Proceedings of the 2019 EMNLP and the 9th IJCNLP (System Demonstrations) , pages 103 108 Hong Kong, China, November 3 7, 2019. c 2019 Association for Computational Linguistics
The recent studies on interactive MT [1], [2] have shown that NMT [3] can significantly surpass PB-SMT [4]. The MT researchers have also investigated integration of advance machine learning features into the interactive MT models in order to further minimise human efforts in translation [5], [6]. In a different MT research context, Nadejde et
The recent studies on interactive MT [1], [2] have shown that NMT [3] can significantly surpass PB-SMT [4]. The MT researchers have also investigated integration of advance machine learning features into the interactive MT models in order to further minimise human efforts in translation [5], [6]. In a different MT research context, Nadejde et
translate in a exible translation manner be-yondleft-to-right. However, theytypicallysuf-fer from limitations in translation efciency and quality due to the reliance on LCD. In this work, we propose a novel BiTIIMT system, Bilingual Text-Inlling for Interactive Neural Machine Translation. The key idea to BiTI-IMT is the Bilingual Text-inlling

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