14,593 research outputs found

    What's New in Statistical Machine Translation

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    Deep Learning: Our Miraculous Year 1990-1991

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    In 2020, we will celebrate that many of the basic ideas behind the deep learning revolution were published three decades ago within fewer than 12 months in our "Annus Mirabilis" or "Miraculous Year" 1990-1991 at TU Munich. Back then, few people were interested, but a quarter century later, neural networks based on these ideas were on over 3 billion devices such as smartphones, and used many billions of times per day, consuming a significant fraction of the world's compute.Comment: 37 pages, 188 references, based on work of 4 Oct 201

    Special Libraries, April 1963

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    Volume 54, Issue 4https://scholarworks.sjsu.edu/sla_sl_1963/1003/thumbnail.jp

    Towards a corpus-based, statistical approach of translation quality : measuring and visualizing linguistic deviance in student translations

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    In this article we present a corpus-based statistical approach to measuring translation quality, more particularly translation acceptability, by comparing the features of translated and original texts. We discuss initial findings that aim to support and objectify formative quality assessment. To that end, we extract a multitude of linguistic and textual features from both student and professional translation corpora that consist of many different translations by several translators in two different genres (fiction, news) and in two translation directions (English to French and French to Dutch). The numerical information gathered from these corpora is exploratively analysed with Principal Component Analysis, which enables us to identify stable, language-independent linguistic and textual indicators of student translations compared to translations produced by professionals. The differences between these types of translation are subsequently tested by means of ANOVA. The results clearly indicate that the proposed methodology is indeed capable of distinguishing between student and professional translations. It is claimed that this deviant behaviour indicates an overall lower translation quality in student translations: student translations tend to score lower at the acceptability level, that is, they deviate significantly from target-language norms and conventions. In addition, the proposed methodology is capable of assessing the acceptability of an individual student’s translation – a smaller linguistic distance between a given student translation and the norm set by the professional translations correlates with higher quality. The methodology is also able to provide objective and concrete feedback about the divergent linguistic dimensions in their text

    Special Libraries, December 1959

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    Volume 50, Issue 10https://scholarworks.sjsu.edu/sla_sl_1959/1009/thumbnail.jp

    Special Libraries, September 1957

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    Volume 48, Issue 7https://scholarworks.sjsu.edu/sla_sl_1957/1006/thumbnail.jp

    Special Libraries, May-June 1958

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    Volume 49, Issue 5https://scholarworks.sjsu.edu/sla_sl_1958/1004/thumbnail.jp
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