We present a comparison of automatic metrics against human evaluations of translation quality in several scenarios which were unexplored up to now. Our experimentation was conducted on translation hypotheses that were...
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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,...
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During the last few years, the statistical approach has found widespread use in machine translation, in particular for spoken language. In many comparative evaluations of automatic speech translation, the statistical ...
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During the last few years, the statistical approach has found widespread use in machine translation, in particular for spoken language. In many comparative evaluations of automatic speech translation, the statistical approach was found to be significantly superior to the existing conventional approaches. The paper will present the main components of a statistical machine translation system (such as alignment and lexicon models, training procedure, generation of the target sentence) and summarize the progress made so far. We will conclude with a roadmap for future research on spoken language translation.
In addition to speech recognition and syntactic parsing, during the last 10 years, the statistical approach has found widespread use in machine translation of both written language and spoken language. In many compara...
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In addition to speech recognition and syntactic parsing, during the last 10 years, the statistical approach has found widespread use in machine translation of both written language and spoken language. In many comparative evaluations, the statistical approach was found to be competitive or superior to the existing conventional approaches. Since the first statistical approach was proposed at the end of the 80s, many attempts have been made to improve the state of the art. Like other natural language processing tasks, machine translation requires four major components: a decision rule, a set of probability models, a training criterion and an efficient generation of the target sentence. We will consider each of these four components in more detail and point out promising research directions.
Cross-lingual alignment methods for monolingual language representations have received notable attention in recent years. However, their use in machine translation pre-training remains scarce. This work tries to shed ...
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This paper is based on the work carried out in the framework of the Verbmobil project, which is a limited-domain speech translation task (German-English). In the final evaluation, the statistical approach was found to...
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Whenever the quality provided by a machine translation system is not enough, a human expert is required to correct the sentences provided by the machine translation system. In such a setup, it is crucial that the syst...
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ISBN:
(纸本)9782951740884
Whenever the quality provided by a machine translation system is not enough, a human expert is required to correct the sentences provided by the machine translation system. In such a setup, it is crucial that the system is able to learn from the errors that have already been corrected. In this paper, we analyse the applicability of discriminative ridge regression for learning the log-linear weights of a state-of-the - art machine translation system underlying an interactive machine translation framework, with encouraging results.
Inspired by previous chunk-level reordering approaches to statistical machine translation, this paper presents two methods to improve the reordering at the chunk level. By introducing a new lattice weighting factor an...
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Phoneme-based acoustic modeling of large vocabulary automatic speech recognition takes advantage of phoneme context. The large number of context-dependent (CD) phonemes and their highly varying statistics require tyin...
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We address for the first time unsupervised training for a translation task with hundreds of thousands of vocabulary words. We scale up the expectation-maximization (EM) algorithm to learn a large translation table wit...
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