White Papers

 Integrating SDL Trados 2007 and PROMT LSP 9.5 into a translation workflow

Oleg Vigodsky, Head of Argonaut Translation Agency

A detailed description of integrating SDL Trados 2007 and PROMT LSP 9.5 software tools into a translation workflow is provided.

 Integrating SDL Trados 2007 and PROMT LSP 9.5 into a translation workflow

Oleg Vigodsky, Head of Argonaut Translation Agency

A detailed description of integrating SDL Trados Studion 2011 and PROMT LSP 9.5 software tools into a translation workflow is provided.

 Machine Translation as a translator's tool

Oleg Vigodsky, Head of Argonaut Translation Agency

This presentation covers following issues:

  • Integrating MT (PROMT) and CATs into a translation workflow,
  • Terminology development and MT customization,
  • Consistency management (at terminology and style levels),
  • Benefits of using MT. 

 Creating an Automated System for Translation of User-Generated Content 

Alexander Molchanov, Leonid Evdokimov

Dialog Conference 2013, Russia, Moscow

29.05– 02.06.2013

This paper describes fast implementation of a hybrid automated translation system for processing user-generated content. We report on engine customization for TripAdvisor, the world's largest travel website. Due to the growing potential of the Russian travel market, TripAdvisor created the Russian version of its website and decided to translate all English reviews into Russian. PROMT, a leading provider of industrial MT solutions, was selected as MT vendor for the English-Russian language pair. According to the client's request we had to perform customization within a short period.

Machine Translation of User Generated Content

Julia Epiphantseva, Head of Business Development

USA, Seattle, TAUS User Conference 2012


Julia Epiphantseva talks about where PROMT finds data, how they train an MT engine and how they evaluate translation output in the case of Machine Translation User generated content.



PROMT DeepHybrid System for WMT12 Shared Translation Task

Alexander Molchanov, Head of Statistical Research Team

Montreal, Quebec, Canada, Seventh Workshop on Statistical Machine Translation


This paper describes the PROMT submission for the WMT12 shared translation task. We participated in two language pairs: English-French and English-Spanish. The translations were made using the PROMT DeepHybrid engine, which is the first hybrid version of the PROMT system. We report on improvements over our baseline RBMT output both in terms of automatic evaluation metrics and linguistic analysis.



Flexible and efficient management of translation quality

Julia Epiphantseva, Head of Linguistics Research Team

Berlin, Translingual Europe 2010


One of advantages of our systems is the high level of adaptibility to the different requirements of a customer. It’s because of flexibility of translation pipeline and a variety of tools which help to adjust the translation process for the specific domain and to get high-quality translation. Depending on necessity to process documents with different structure the different format translators and text preprocessors can be used. For example, the preprocessors can be used when the text contains some symbol sequences which should not to be translated or should be translated in some special way, like e-mail addresses, special escape sequences for selecting of the fragments of text.


A Brief Guide to PROMT Machine Translation Technology 

This white paper focuses on PROMT machine translation technology. It provides a background of machine translation (MT), the advantages of MT technology used by PROMT, functionality, types of translation demands, and PROMT customization tools.

"MT systems work with natural language - a data set that is infinitely variable, ambiguous, and structurally complex. To translate adequately, an MT system must encode knowledge of hundreds of syntactic patterns, variations, and exceptions, as well as relationships among these patterns. Machine translation software should be equipped with ever-changing vocabulary and specific semantic knowledge about the usage patterns of tens of thousands of words. The system must ensure the accurate identification of parts of speech and the grammatical characteristics of words which may, in different contexts, be nouns, verbs, or adjectives, each having many possible translations. Translation also requires a vast store of knowledge about the world, the intent of the communication, and the subject matter.”


"How the Computer Translates"
Svetlana Sokolova
President of PROMT
Ph.D Computer Science

Machine translation is not as simple as it seems at first glance. It is not just a matter of importing large dictionaries into the machine translation engine. The article explains "How the Computer Translates," how the machine translation engine stores rules, recognizes common collocations, and how the engine can be configured to yield optimal results. 


"Machine Translation for Cross-Language Social Media"

Jordi Carrera, Olga Beregovaya, Alex Yanishevsky, 2008

User-generated content available in weblogs and social media a) contains high noise levels, b) is domain independent, c) is generated fast, d) is available in large quantities and d) is inherently focused on information content and knowledge sharing. Thanks to the new Internet culture, which emphasizes accessibility, openness and active participation, communication needs are less stringent but require faster response and must preserve information content. These properties make user-generated content suitable for machine translation and, more specifically, hybrid machine translation, which combines knowledge representation with statistical modeling. In this article we present a qualitative study of data extracted from the Social Media Dataset: we analyze how naturally occurring phenomena can affect machine translation quality and we show how new hybrid approaches may successfully preserve semantics while at the same time achieving near-optimal levels of linguistic fluency.

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PROMT is a world leading provider of automated translation software. The company develops PROMT translation software and dictionaries that have received numerous awards from leading computer magazines. PROMT offers translation solutions for the home and business use, as well as for Internet and corporate intranets.

PROMT provides machine translation for 16 languages: English, Russian, German, French, Spanish, Italian, Portuguese, Chinese in two variants, Ukrainian, Kazakh, Turkish, Bulgarian, Latvian, Japanese and Polish, with a total of 64 translation directions

The Ukrainian, Latvian and Polish language pairs included in the PROMT solutions are developed by Trident Software.

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