César Martínez

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Speech-input translation can be properly approached as a pattern recognition problem by means of statistical alignment models and stochastic finite-state transducers. Under this general framework, some specific models are presented. One of the features of such models is their capability of automatically learning from training examples. Moreover, the(More)
Recurrent connectionist models provide a method to represent dynamic patterns in a neural network. In this work we present a method for chromosome classification based on an almost unexplored neural network technique for this task. A partially recurrent con-nectionist model, the Elman network, is managed to capture the dark and light band patterns of the(More)
Picramnia thomasii, a new species from the state of Guerrero, Mexico is described and illustrated. It is related to P. guerrerensis, but differs by having leaflets with indumentum on the underside, a larger staminate inflorescence with more glomeruli, petals with a different shape and color, longer stamens, fruits with indument, smaller seeds, and the(More)
Computer-Assisted Translation systems can be used by human translators to increase their productivity. In these systems, the computer suggests portions of target sentence that can be accepted or amended by a human translator. In the present work we will introduce speech as a novel way to interact with these systems. The rational behind this approach is to(More)
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