1. Articles in category: Machine Translation

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    1. 2005 ACL Lifetime Achievement Award

      Home arrow News arrow Main Menu Home News Conferences Membership Publications CL Journal Resources Affiliations SIGs About the ACL Contact Us Search NLP/CL Universe ACL Policies PDF Print Martin Kay: ACL Award Winner! The ACL Lifetime Achievement Award The ACL Lifetime Achievement Award was instituted on the occasion of the 40th anniversary meeting of the Association. The award will henceforth be presented for scientific ac
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    2. 2006 ACL Lifetime Achievement Award

      One of the highlights of COLING/ACL 2006 was the presentation of the 2006 ACL Lifetime Achievement Award to: Eva Hajicova The following is an excerpt from the introduction made by Jun'ichi Tsujii (president of the ACL) at the COLING/ACL 2006 award ceremony. I first met Eva, 26 years ago, at Coling in Tokyo, 1980. I had just started my career as researcher then, while she was already an established researcher, a member of ICCL (International Committee of Computational Linguistics) and the representative, the banner carrier of the legendary Prague school of linguistics. Prague is the birth place ...
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    3. EMNLP-CoNLL 2007 Call for Papers

      Home arrow News arrow Main Menu Home News Conferences Membership Publications CL Journal Resources Affiliations SIGs About the ACL Contact Us Search NLP/CL Universe ACL Policies PDF Print EMNLP-CoNLL 2007 Conference on Empirical Methods in Natural Language Processing Conference on Computational Natural Language Learning June 28-30, 2007 Prague, Czech Republic http://cs.jhu.edu/EMNLP-CoNLL-2007 The annual EMNLP and CoNLL conferenc
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    4. Particle filtering versus beam search

      I had a very interesting discussion at NIPS with Vikash Mansingka about beam search and particle filtering. Much of what is below is a result of this conversation and he deserves much credit. In a very real sense, particle filtering can be seen (for many models) as a sort of stochastic beam search. Just to set the stage, let's talk about generic beam search: The key variant in beam search algorithms is the score function that's used. The most naive is just path cost---how much did we have to pay
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    5. Implementing NLP projects for noncentral languages: instructions for funding bodies, strategies for developers

      Abstract  This research begins by distinguishing a small number of “central” languages from the “noncentral languages”, where centrality is measured by the extent to which a given language is supported by natural language processing tools and research. We analyse the conditions under which noncentral language projects (NCLPs) and central language projects are conducted. We establish a number of important differences which have far-reaching consequences for NCLPs. In order to overcome the difficulties inherent in NCLPs, traditional research strategies have to be reconsidered. Successful styles of scientific cooperation, such as those found in open-source software development or in the development of ...
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      Mentions: Taiwan
    6. Generating with lexical functional grammars

      A process for generating with unification based grammars such as Lexical Functional Grammars which uses construction and analysis of generation guides to determine internal facts and eliminate incomplete edges prior to constructing a generation chart. The generation guide can then be used in the construction of the generation chart to efficiently generate with unification-based grammars such as Lexical Functional Grammars. The generation guide is an instance of a grammar that has been specialized to the input and only contains those parts of the grammar that are relevant to the input. When the generation guide is analyzed to determine internal facts ...
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    7. Recent advances on NLP research in Harbin Institute of Technology

      Abstract  In the 1960s, the researchers of Harbin Institute of Technology (HIT) attempted to do relevant research on natural language processing. With more than 40-year’s effort, HIT has already established three research laboratories for Chinese information processing, i.e. the Machine Intelligence and Translation Laboratory (MI&T; Lab), the Intelligent Technology and Natural Language Processing Laboratory (ITNLP) and the Information Retrieval Laboratory (IR-Lab). At present, it has a well-balanced research team of over 200 persons, and the research interests have extended to language processing, machine translation, text retrieval and other fields. Harbin Institute of Technology has accumulated a batch of ...
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    8. Systems and methods for using statistical techniques to reason with noisy data

      Systems and methods are presented that enable logical reasoning even in the presence of noisy (inconsistent) data. The knowledge base is processed in order to make it consistent and is also compiled. This processing includes checking and correcting spelling, removing stopwords, performing, grouping words of similar and related meaning, and compacting the knowledge base. A robot can use the processed knowledge base to perform many different types of tasks, such as answering a query, determining a course of action that is designed to achieve a particular goal, and determining its own location.
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    9. Translation out of English

      If you look at MT papers published in the *ACL conferences and siblings, I imagine you'll find a cornucopia of results for translating into English (usually, from Chinese or Arabic, though sometimes from German or Spanish or French, if the corpus used is from EU or UN or de-news). The parenthetical options are usually just due to the availability of corpora for those languages. The former two are due to our friend DARPA's interest in translating from Chinese and Arabic into English. There are ce
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    10. Statistical memory-based translation system

      A statistical machine translation (MT) system may include a translation memory (TMEM) and a decoder. The decoder may translate an input text segment using a statistical MT decoding algorithm, for example, a greedy decoding algorithm. The system may generate a cover of the input text segment from text segments in the TMEM. The decoder may use the cover as an initial translation in the decoding operation.
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    11. Apparatus and method for selecting a translation word of an original word by using a target language document database

      A machine translation apparatus includes a plurality of target language document databases used for a translation from an original language to a target language. A database control unit assigns a priority degree to each of the plurality of target language document databases, and indicates a target language document database of the highest priority degree. A translation word generation unit generates a plurality of translation word candidates of an original word for the translation. A translation word learning unit selects a translation word from the plurality of translation word candidates by using the target language document database indicated by the database ...
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    12. System and method of word graph matrix decomposition

      Disclosed is a system and method of decomposing a lattice transition matrix into a block diagonal matrix. The method is applicable to automatic speech recognition but can be used in other contexts as well, such as parsing, named entity extraction and any other methods. The method normalizes the topology of any input graph according to a canonical form.
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      Mentions: Oracle
    13. Extended FAQ for the Windows Live Translator Beta

        1) Where can I find help with the translator service? Help and FAQ are here. 2) How is the text translated? Text is translated by computer software automatically and without human involvement. Web pages about computer-related topics are translated by Microsoft’s own state-of-the-art statistical machine translation technology which has been trained on large amounts of computer-related data. Web pages about other topics or into languages that are not included in Microsoft’s eight currently supported languages are translated by translation software from Systran. 3) Why is the quality of the translation not as good as I would like it ...
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    14. Introducing: Windows Live Translator Beta

      There has been some great coverage recently on the beta release of our new online translation service. In this post I would like to provide you with information regarding Microsoft’s entry into the free online machine translation field – straight from the horse’s mouth, figuratively speaking. The URL of the translation home page is http://translator.live.com, where you can issue requests for text and web page translations: Note that a check box option labeled Computer-related content allows you to get better-adapted translations for (computer-) technical text, provided by Microsoft Research’s own statistical machine translation engine. This ...
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    15. Machine Translation group at Microsoft Research

      Microsoft Research’s Machine Translation (MSR-MT) group has been among the leading research organizations in the machine translation space for over 8 years, and some of the foundational work in natural language processing at MSR began over 16 years ago. The team’s approach to machine translation integrates linguistic features with state-of-the-art statistical machine translation algorithms. The team’s focus has always been on automatically acquiring translation knowledge from bilingual corpora, i.e., parallel data consisting of original source language sentences and their corresponding translations by human translators. About 3 years ago, the team’s focus shifted from a purely ...
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    16. Welcome to the Machine Translation team blog!

      Welcome to our blog! We are very excited to bring to you news and insights into work (and fun) at the Machine Translation (MT) Group within Microsoft Research. We have great mix of researchers, developers, testers, program managers, linguists, designers and product managers working on MT here, and we are pleased to launch this blog as a way to connect with customers, partners and other friends of MT. We hope this will provide greater insight into the work we do and who we are, and we are very excited to be talking to you. Machine Translation (MT), to those that ...
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      Mentions: Microsoft
    17. Tokenizer for a natural language processing system

      The present invention is a segmenter used in a natural language processing system. The segmenter segments a textual input string into tokens for further natural language processing. In accordance with one feature of the invention, the segmenter includes a tokeinzer engine that proposes segmentations and submits them to a linguistic knowledge component for validation. In accordance with another feature of the invention, the segmentation system includes language specific data that contains a precedence hierarchy for punctuation. If proposed tokens in the input string contain punctuation, they can illustratively be broken into subtokens based on the precedence hierarchy.
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    7897-7920 of 8094 « 1 2 ... 327 328 329 330 331 332 333 ... 336 337 338 »
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