Multi-Task Minimum Error Rate Training for SMT
نویسندگان
چکیده
منابع مشابه
Multi-Task Minimum Error Rate Training for SMT
We present experiments on multi-task learning for discriminative training in statistical machine translation (SMT), extending standardminimum-error-rate training (MERT) by techniques that take advantage of the similarity of related tasks. We apply our techniques to German-toEnglish translation of patents from 8 tasks according to the International Patent Classification (IPC) system. Our experim...
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Modern Statistical Machine Translation (SMT) systems make their decisions based on multiple information sources, which assess various aspects of the match between a source sentence and its possible translation(s). Tuning a SMT system consists in finding the right balance between these sources so as to produce the best possible output, and is usually achieved through Minimum Error Rate Training ...
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The most commonly used method for training feature weights in statistical machine translation (SMT) systems is Och’s minimum error rate training (MERT) procedure. A well-known problemwith Och’s procedure is that it tends to be sensitive to small changes in the system, particularly when the number of features is large. In this paper, we quantify the stability of Och’s procedure by supplying diff...
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Minimum Error Rate Training (MERT) remains one of the preferred methods for tuning linear parameters in machine translation systems, yet it faces significant issues. First, MERT is an unregularized learner and is therefore prone to overfitting. Second, it is commonly used on a noisy, non-convex loss function that becomes more difficult to optimize as the number of parameters increases. To addre...
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Minimum error rate training is a crucial component to many state-of-the-art NLP applications, such as machine translation and speech recognition. However, common evaluation functions such as BLEU or word error rate are generally highly non-convex and thus prone to search errors. In this paper, we present LP-MERT, an exact search algorithm for minimum error rate training that reaches the global ...
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ژورنال
عنوان ژورنال: The Prague Bulletin of Mathematical Linguistics
سال: 2011
ISSN: 1804-0462,0032-6585
DOI: 10.2478/v10108-011-0015-0