TAILIEUCHUNG - Báo cáo khoa học: "Active learning for interactive machine translation"

Translation needs have greatly increased during the last years. In many situations, text to be translated constitutes an unbounded stream of data that grows continually with time. An effective approach to translate text documents is to follow an interactive-predictive paradigm in which both the system is guided by the user and the user is assisted by the system to generate error-free translations. Unfortunately, when processing such unbounded data streams even this approach requires an overwhelming amount of manpower. . | Active learning for interactive machine translation Jesus Gonzalez-Rubio and Daniel Ortiz-Martinez and Francisco Casacuberta D. de Sistemas Informaticos y Computation U. Politecnica de Valencia C. de Vera s n 46022 Valencia Spain jegonzalez dortiz fcn @ Abstract Translation needs have greatly increased during the last years. In many situations text to be translated constitutes an unbounded stream of data that grows continually with time. An effective approach to translate text documents is to follow an interactive-predictive paradigm in which both the system is guided by the user and the user is assisted by the system to generate error-free translations. Unfortunately when processing such unbounded data streams even this approach requires an overwhelming amount of manpower. Is in this scenario where the use of active learning techniques is compelling. In this work we propose different active learning techniques 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 Translation needs have greatly increased during the last years due to phenomena such as globalization and technologic development. For example the European Parliament1 translates its proceedings to 22 languages in a regular basis or Project Syndicate2 that translates editorials into different languages. In these and many other examples data can be viewed as an incoming unbounded stream since it grows continually with time Levenberg et al. 2010 . Manual translation of such streams of data is extremely expensive given the huge volume of translation required 1 http 2http therefore various automatic machine translation methods have been proposed. However automatic statistical machine translation SMT systems are far from generating error-free translations and their outputs usually .

• Báo cáo khoa học
• Active learning
• interactive machine translation
• Jesus Gonz
• scientific reports
• model language
• process natural language
• Promoting active learning and strategies
• Promoting active learning for students at Ba Ria Vung Tau
• Strategies students at Ba Ria Vung Tau
• Effective learning method
• Current learning styles
• Graduation thesis
• English language graduation thesis
• English class
• Learning in English class
• Student performance in English class
• Journal of technology and science education
• Effects of active learning methodologies
• The students’ emotions
• self efficacy beliefs
• Science distance learning course
• The positive emotions
• Journal of Automation and Control Engineering
• Active learning in motor control and matlab simulation
• Active learning in motor control
• Servo motors of the simulation of neural networks
• Motion of a robot arm
• Enhancing moodle for active learning
• Interactive multimedia
• Interactive media
• Quizventure game
• Moodle native counterpart
• A Combination of Active Learning
• Semi supervised Learning Starting
• Positive and Unlabeled Examples for Word Sense Disambiguation An Empirical Study on Japanese Web Search Query
• báo cáo khoa học
• báo cáo ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Information Sciences
• Intelligent tutoring system
• Supporting active learning
• Predictive parsing learning
• Formal language processing
• BMC Bioinformatics
• Pathological image classification
• Atrous convolution
• Deep learning
• Multiscale feature
• Learning stations
• Active teaching learning
• Inquiry teaching
• Primary education
• Cooperative learning
• Machine learning
• Drug development
• Computational biology
• Drug discovery
• Using Smaller Constituents Rather Than Sentences
• Japanese Dependency Parsing
• ngôn ngữ tự nhiên
• Bucking the Trend
• Large Scale Cost Focused Active Learning
• Statistical Machine Translation
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• Graphical Models
• Good Seed Makes a Good Crop
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• Language Modeling
• Active Learning Based Elicitation
• Semi Supervised Word Alignment
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• An Active Learning Approach
• Finding Related Terms
• David Vickrey
• Multilingual Statistical Machine Translation
• Gholamreza Haffari and Anoop Sarkar
• Evaluating the Impact
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• Semi Supervised Active Learning
• Sequence Labeling
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• Multi Task Active Learning
• Linguistic Annotations
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