916 resultados para Linguistic interactionism


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In this paper a method to incorporate linguistic information regarding single-word and compound verbs is proposed, as a first step towards an SMT model based on linguistically-classified phrases. By substituting these verb structures by the base form of the head verb, we achieve a better statistical word alignment performance, and are able to better estimate the translation model and generalize to unseen verb forms during translation. Preliminary experiments for the English - Spanish language pair are performed, and future research lines are detailed. © 2005 Association for Computational Linguistics.

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M. Galea and Q. Shen. Linguistic hedges for ant-generated rules. Proceedings of the 15th International Conference on Fuzzy Systems, pages 9105-9112, 2006.

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M. Galea and Q. Shen. Simultaneous ant colony optimisation algorithms for learning linguistic fuzzy rules. A. Abraham, C. Grosan and V. Ramos (Eds.), Swarm Intelligence in Data Mining, pages 75-99.

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Instytut Filologii Angielskiej

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English & Polish jokes based on linguistic ambiguity are constrasted. Linguistic ambiguity results from a multiplicity of semantic interpretations motivated by structural pattern. The meanings can be "translated" either by variations of the corresponding minimal strings or by specifying the type & extent of modification needed between the two interpretations. C. F. Hockett's (1972) translatability notion that a joke is linguistic if it cannot readily be translated into other languages without losing its humor is used to interpret some cross-linguistic jokes. It is claimed that additional intralinguistic criteria are needed to classify jokes. By using a syntactic representation, the humor can be explained & compared cross-linguistically. Since the mapping of semantic values onto lexical units is highly language specific, translatability is much less frequent with lexical ambiguity. Similarly, phonological jokes are not usually translatable. Pragmatic ambiguity can be translated on the basis of H. P. Grice's (1975) cooperative principle of conversation that calls for discourse interpretations. If the distinction between linguistic & nonlinguistic jokes is based on translatability, pragmatic jokes must be excluded from the classification. Because of their universality, pragmatic jokes should be included into the linguistic classification by going beyond the translatability criteria & using intralinguistic features to describe them.

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Unpublished paper, written in 1996.

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En los últimos años los críticos han dedicado mucha atención a la investigación de las voces conflictivas de la obra dramática de Lope de Vega. Se ha enfatizado en particular el papel subversivo de la lengua, sobre todo desde la perspectiva de la teoría de los actos de habla. Este artículo sobre El perro del hortelano opera dentro de un marco teórico similar para analizar cómo las retóricas poco estables del honor y del amor conducen a una desintegración de estos códigos artificiales linguísticos. Además, sugieren la presencia de una inestabilidad social colectiva más siniestra y más comprometida fuera del escenario. La ironía dramática, que sostiene el encubrimiento y la revelación de la 'verdad' a lo largo de la obra, lleva a un desenlace más liminal que cerrado y, quizás, permite la recuperación de unas voces significativas que penetren más allá del tiempo y la época en que fue escrita la obra.

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This chapter, in a prize-winnng volume, examines Milton's bilingual practices in relation to his translation of Horace, Odes 1, 5 and the 1645 volume as a whole. Drawing upon seventeenth-century pedagogical practice and methodology it examines the potential importance of his schooling and university exercises to the methodology of Paradise Lost.

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For many applications of emotion recognition, such as virtual agents, the system must select responses while the user is speaking. This requires reliable on-line recognition of the user’s affect. However most emotion recognition systems are based on turnwise processing. We present a novel approach to on-line emotion recognition from speech using Long Short-Term Memory Recurrent Neural Networks. Emotion is recognised frame-wise in a two-dimensional valence-activation continuum. In contrast to current state-of-the-art approaches, recognition is performed on low-level signal frames, similar to those used for speech recognition. No statistical functionals are applied to low-level feature contours. Framing at a higher level is therefore unnecessary and regression outputs can be produced in real-time for every low-level input frame. We also investigate the benefits of including linguistic features on the signal frame level obtained by a keyword spotter.