History and experience of using machine translation. Yandex lecture
3r33411. 3r3-31. In September, the sixth Hyperbaton was held - a Yandex conference on everything related to technical documentation. We will publish several lectures from Hyperbaton, which, in our opinion, may be the most interesting for Habr readers.
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3r33411. Svetlana Kayushina, Head of Documentation and Localization:
3r33411. - It seems that there are no more people in the world who translate manually. Today we want to talk about the tools and approaches that help companies organize an effective localization process, and translators make it easier for them to solve their everyday tasks. Today we will talk about machine translation, the evaluation of the effectiveness of machine engines and automated translation systems for translators.
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3r33411. Let's start with the report of our colleagues. I invite Irina Rybnikov and Anastasia Ponomareva - they will tell you about Yandex’s experience in introducing machine translation into our localization processes. will be devoted to this topic. The next report is 3r30000. . Be prepared that there are still difficulties, engine developers are working together to solve difficulties, but while they are still encountered.
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3r33411. I would like to understand what awaits us in the future. But in fact, this is no longer any further, but our present time, what is happening here and now. We all rather need customization under our terminology, under our texts, and this is something that is now becoming public. Now everyone is working to ensure that you do not go inside the company, do not agree with the developers of a specific engine, how to optimize it for you. You can receive it in public open engines on API.
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3r33411. Customization is not only in text, but also in terminology, to customize the terminology for your own needs. This is quite an important point. The second topic is interactive translation. When the translator translates the text, the technology allows him to predict the following words based on the source language, the source text. This Auger can greatly facilitate the work.
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3r33411. The fact that now is really expensive. Everyone thinks how to train some engines much more effectively with smaller amounts of text. This is what happens everywhere and runs everywhere. I think the topic is very interesting, and then it will be even more interesting.
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3r33411. We have collected several articles that may interest you. Thank!
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Two models are better than one. Experience Yandex. Translator
3r33411. - 3r3395. As Yandex used artificial intelligence technology to translate web pages 3r30000.
3r33411. - 3r33399. Machine translate. From the cold war to diplerning
3r3407. 3r33411. 3r33411. 3r3404. ! function (e) {function t (t, n) {if (! (n in e)) {for (var r, a = e.document, i = a.scripts, o = i.length; o-- ;) if (-1! == i[o].src.indexOf (t)) {r = i[o]; break} if (! r) {r = a.createElement ("script"), r.type = "text /jаvascript", r.async =! ? r.defer =! ? r.src = t, r.charset = "UTF-8"; var d = function () {var e = a.getElementsByTagName ("script")[0]; e.parentNode.insertBefore (r, e)}; "[object Opera]" == e.opera? a.addEventListener? a.addEventListener ("DOMContentLoaded", d! ): d ()}}} t ("//mediator.mail.ru/script/2820404/"""_mediator") () (); 3r3405. 3r33411. 3r3407. 3r33411. 3r33411. 3r33411. 3r33411.
It may be interesting
weber
Author22-10-2018, 13:36
Publication DateDevelopment / Machine learning
Category- Comments: 1
- Views: 501
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