[PDF] Top 20 Active Learning and Crowd-Sourcing for Machine Translation
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Active Learning and Crowd-Sourcing for Machine Translation
... our crowd- sourcing ...via crowd- ...language translation being a strik- ing ...chine translation a HIT is a task where a turker is provided with one or more sentences in the source ... See full document
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Active Learning for Interactive Neural Machine Translation of Data Streams
... of active learning techniques to the translation of unbounded data streams via interactive neural machine ...neural machine translation ...neural machine ... See full document
10
Active Learning for Multilingual Statistical Machine Translation
... Statistical machine translation (SMT) models require bilingual corpora for train- ing, and these corpora are often multi- lingual with parallel text in multiple lan- guages ...an active ... See full document
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Active Learning for Statistical Phrase based Machine Translation
... Statistical machine translation (SMT) mod- els need large bilingual corpora for train- ing, which are unavailable for some language ...of active learning for SMT. We use active ... See full document
9
Selecting Syntactic, Non redundant Segments in Active Learning for Machine Translation
... In this work, we propose two methods that aim to solve these two problems and improve the efficiency and reliability of segment-based active learning for SMT (§4). For the problem of overlapping phrases, we ... See full document
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A Semi Supervised Batch Mode Active Learning Strategy for Improved Statistical Machine Translation
... the translation phrase table and target language model ...phrase translation probabilities, the maximum forward and reverse word-level lexical translation probabilities, num- ber of competing target ... See full document
9
Bucking the Trend: Large Scale Cost Focused Active Learning for Statistical Machine Translation
... Snow et al. (2008) explored the use of the Ama- zon Mechanical Turk (MTurk) web service for gathering annotations for a variety of natural lan- guage processing tasks and recently MTurk has been shown to be a quick, ... See full document
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Enlarging Monolingual Dictionaries for Machine Translation with Active Learning and Non-Expert Users
... an active learn- ing mechanism in her transfer rule refinement system, asking the user to validate different translations deduced from the initial hypoth- ...this active learning approach has not yet ... See full document
8
Confidence based Active Learning Methods for Machine Translation
... Another important novel feature in our work is the addition of real post-editions to the MT train- ing data, as opposed to simulated post-editions (human reference translations) as in previous work on AL for MT. As we ... See full document
6
Active learning for interactive machine translation
... the translation qual- ity, in terms of BLEU, across different data blocks for the three sampling strategies described in sec- tion 5, namely, dynamic confidence sampling (DCS), n-gram coverage sampling (NS) and ... See full document
10
Online Gaming for Crowd sourcing Phrase equivalents
... paraphrases. PEs are useful for many NLP systems from simple language modelling and smoothing, to complex Machine Translation technology for generation of a surface form in the target language. Most ... See full document
10
Proceedings of the Human Informed Translation and Interpreting Technology Workshop (HiT IT 2019)
... generated active discussions between listeners and ...and machine evaluation of machine translation; using NLP, automatic tools and techniques to study and extract meaningful patterns from ... See full document
10
Sourcing the Crowd for a Few Good Ones: Event Type Detection
... supervised learning approaches relying on large amounts of manually annotated training data collected by domain ...web-based crowd can provide data for the construction of large-scale LRs in a faster, ... See full document
10
Big Data Overview for Twister2 Tutorial
... This is the “business logic” of application and where you find machine learning algorithms like clustering. Mahout , MLlib , MLbase are in Apache for Hadoop and Spark processing; R is a central library from ... See full document
123
A Machine Learning Method to Distinguish Machine Translation from Human Translation
... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, et al. 2007. Moses: Open source toolkit for statistical ... See full document
7
Wikiaudia: Crowd-sourcing the Production of Audio and Digital Books
... Abstract–Audiobooks are an indispensable aid in making books accessible to people with special needs such as visually challenged, elderly and those afflicted with problems of dyslexia and agraphia. Audiobooks are ... See full document
6
Multitude based Quiz System: Targeted Crowd Sourcing.
... The present online quiz systems are not using any algorithm to evaluate the efficiency and also are not using the benefits of crowd as well. The present online quiz systems are not considering the performances of ... See full document
5
Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
... in machine learning research, the remainder of the survey addresses our second goal: to provide the reader with best practices for crowdsourcing by drawing deeply on the vast and cross- disciplinary ... See full document
46
Comparing a Hand crafted to an Automatically Generated Feature Set for Deep Learning: Pairwise Translation Evaluation
... a learning framework for ranking translations in parallel settings, given representations of transla- tion outputs and a reference ...the machine-generated translation as well, by using pre-trained ... See full document
9
Social implications of crowd sourcing in rural Scotland
... of crowd workers on the MTurk crowdsourcing platform reported that more than one-third of them are from India and are typically young and highly educated ... See full document
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