961 resultados para 380200 Linguistics


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Language Documentation and Description as Language Planning Working with Three Signed Minority Languages Sign languages are minority languages that typically have a low status in society. Language planning has traditionally been controlled from outside the sign-language community. Even though signed languages lack a written form, dictionaries have played an important role in language description and as tools in foreign language learning. The background to the present study on sign language documentation and description as language planning is empirical research in three dictionary projects in Finland-Swedish Sign Language, Albanian Sign Language, and Kosovar Sign Language. The study consists of an introductory article and five detailed studies which address language planning from different perspectives. The theoretical basis of the study is sociocultural linguistics. The research methods used were participant observation, interviews, focus group discussions, and document analysis. The primary research questions are the following: (1) What is the role of dictionary and lexicographic work in language planning, in research on undocumented signed language, and in relation to the language community as such? (2) What factors are particular challenges in the documentation of a sign language and should therefore be given special attention during lexicographic work? (3) Is a conventional dictionary a valid tool for describing an undocumented sign language? The results indicate that lexicographic work has a central part to play in language documentation, both as part of basic research on undocumented sign languages and for status planning. Existing dictionary work has contributed new knowledge about the languages and the language communities. The lexicographic work adds to the linguistic advocacy work done by the community itself with the aim of vitalizing the language, empowering the community, receiving governmental recognition for the language, and improving the linguistic (human) rights of the language users. The history of signed languages as low status languages has consequences for language planning and lexicography. One challenge that the study discusses is the relationship between the sign-language community and the hearing sign linguist. In order to make it possible for the community itself to take the lead in a language planning process, raising linguistic awareness within the community is crucial. The results give rise to questions of whether lexicographic work is of more importance for status planning than for corpus planning. A conventional dictionary as a tool for describing an undocumented sign language is criticised. The study discusses differences between signed and spoken/written languages that are challenging for lexicographic presentations. Alternative electronic lexicographic approaches including both lexicon and grammar are also discussed. Keywords: sign language, Finland-Swedish Sign Language, Albanian Sign Language, Kosovar Sign Language, language documentation and description, language planning, lexicography

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One of the most challenging tasks in building language resources is the copyright license management. There are several reasons for this. First of all, the current European copyright system is designed to a large extent to satisfy the commercial actors, e.g. publishers, record companies etc. This means that the scope and duration of the rights are very extensive and there are even certain forms of protection that do not exist elsewhere in the world, e.g. database right. On the other hand, the exceptions for research and teaching are typically very narrow.

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Language software applications encounter new words, e.g., acronyms, technical terminology, names or compounds of such words. In order to add new words to a lexicon, we need to indicate their inflectional paradigm. We present a new generally applicable method for creating an entry generator, i.e. a paradigm guesser, for finite-state transducer lexicons. As a guesser tends to produce numerous suggestions, it is important that the correct suggestions be among the first few candidates. We prove some formal properties of the method and evaluate it on Finnish, English and Swedish full-scale transducer lexicons. We use the open-source Helsinki Finite-State Technology to create finitestate transducer lexicons from existing lexical resources and automatically derive guessers for unknown words. The method has a recall of 82-87 % and a precision of 71-76 % for the three test languages. The model needs no external corpus and can therefore serve as a baseline.

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Transductive SVM (TSVM) is a well known semi-supervised large margin learning method for binary text classification. In this paper we extend this method to multi-class and hierarchical classification problems. We point out that the determination of labels of unlabeled examples with fixed classifier weights is a linear programming problem. We devise an efficient technique for solving it. The method is applicable to general loss functions. We demonstrate the value of the new method using large margin loss on a number of multi-class and hierarchical classification datasets. For maxent loss we show empirically that our method is better than expectation regularization/constraint and posterior regularization methods, and competitive with the version of entropy regularization method which uses label constraints.

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We apply the objective method of Aldous to the problem of finding the minimum-cost edge cover of the complete graph with random independent and identically distributed edge costs. The limit, as the number of vertices goes to infinity, of the expected minimum cost for this problem is known via a combinatorial approach of Hessler and Wastlund. We provide a proof of this result using the machinery of the objective method and local weak convergence, which was used to prove the (2) limit of the random assignment problem. A proof via the objective method is useful because it provides us with more information on the nature of the edge's incident on a typical root in the minimum-cost edge cover. We further show that a belief propagation algorithm converges asymptotically to the optimal solution. This can be applied in a computational linguistics problem of semantic projection. The belief propagation algorithm yields a near optimal solution with lesser complexity than the known best algorithms designed for optimality in worst-case settings.

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Identifying translations from comparable corpora is a well-known problem with several applications, e.g. dictionary creation in resource-scarce languages. Scarcity of high quality corpora, especially in Indian languages, makes this problem hard, e.g. state-of-the-art techniques achieve a mean reciprocal rank (MRR) of 0.66 for English-Italian, and a mere 0.187 for Telugu-Kannada. There exist comparable corpora in many Indian languages with other ``auxiliary'' languages. We observe that translations have many topically related words in common in the auxiliary language. To model this, we define the notion of a translingual theme, a set of topically related words from auxiliary language corpora, and present a probabilistic framework for translation induction. Extensive experiments on 35 comparable corpora using English and French as auxiliary languages show that this approach can yield dramatic improvements in performance (e.g. MRR improves by 124% to 0.419 for Telugu-Kannada). A user study on WikiTSu, a system for cross-lingual Wikipedia title suggestion that uses our approach, shows a 20% improvement in the quality of titles suggested.