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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 Automated Corpus Analysis and the Acquisition of Large, Multi-Lingual Knowledge Bases for MT ... Mitamura, Teruko; Nyberg, Eric; Carbonell, Jaime G.. - : Carnegie Mellon University, 2008 BASE Show details 2 Automated Corpus Analysis and the Acquisition of Large, Multi-Lingual Knowledge Bases for MT ... Mitamura, Teruko; Nyberg, Eric; Carbonell, Jaime G.. - : Carnegie Mellon University, 2008 BASE Show details 3 Evaluating an Agglutinative Segmentation Model for ParaMor ... Monson, Christian; Lavie, Alon; Carbonell, Jaime G.. - : Carnegie Mellon University, 2008 BASE Show details 4 Evaluating an Agglutinative Segmentation Model for ParaMor ... Monson, Christian; Lavie, Alon; Carbonell, Jaime G.. - : Carnegie Mellon University, 2008 BASE Show details 5 Linguistic Structure and Bilingual Informants to Induce Machine Translation of Lesser-Resourced Languages ... Monson, Christian; Llitjós, Ariadna Font; Vamshi Ambati. - : Carnegie Mellon University, 2008 BASE Show details 6 Linguistic Structure and Bilingual Informants to Induce Machine Translation of Lesser-Resourced Languages ... Monson, Christian; Llitjós, Ariadna Font; Vamshi Ambati; Levin, Lori; Lavie, Alon; Alvarez, Alison; Aranovich, Roberto; Carbonell, Jaime G.; Frederking, Robert; Peterson, Erik; Probst, Katharina. - : Carnegie Mellon University, 2008 Abstract: Producing machine translation (MT) for the many minority languages in the world is a serious challenge. Minority languages typically have few resources for building MT systems. For many minor languages there is little machine readable text, few knowledgeable linguists, and little money available for mT development. For these reasons, our research programs on minority language MT have focused on leveraging to the maximum extent two resources that are available for minority languages: linguistic structure and bilingual informants. All natural languages contain linguistic structure. And although the details of that linguistic structure vary from language to language, language universals such as context-free syntactic structure and the paradigmatic structure of inflectional morphology, allow us to learn the specific details of a minority language. Similarly, most minority languages possess speakers who are bilingual with the major language of the area. This paper discusses our efforts to utilize linguistic ... Keyword: 80399 Computer Software not elsewhere classified; FOS Computer and information sciences URL: https://dx.doi.org/10.1184/r1/6623216 https://kilthub.cmu.edu/articles/Linguistic_Structure_and_Bilingual_Informants_to_Induce_Machine_Translation_of_Lesser-Resourced_Languages/6623216 BASE Hide details 7 The Universal Parser Architecture for Knowledge-Based Machine Translation ... Tomita, Masaru; Carbonell, Jaime G.. - : Carnegie Mellon University, 2008 BASE Show details 8 The Universal Parser Architecture for Knowledge-Based Machine Translation ... Tomita, Masaru; Carbonell, Jaime G.. - : Carnegie Mellon University, 2008 BASE Show details 9 Lexical and semantic resources for NLP: from words to meanings Gentile, Anna Lisa; Basile, Pierpaolo; Iaquinta, Leo. - : Springer, 2008 BASE Show details

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