854 resultados para López, Gregorio, 1542-1596


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Mención de parte consta al final de la port.

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Hay un ejemplar encuadernado con: Las Siete Partidas del Rey D. Alfonso el Sabio (NP34/2).

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Hay un ejemplar encuadernado con el volumen facticio XVIII/2778

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Hay un ejemplar encuadernado con: Las siete partidas del rey D. Alfonso el Sabio (NP34/3).

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Hay un ejemplar encuadernado con: Las siete partidas del rey D. Alfonso el Sabio (NP34/3).

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En ángulo inf. izquierdo: "Paso a la[...] / de / Hacienda pub[...]"

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En este proyecto se estudiaron los requerimientos de diseño y desarrollo necesarios para la creación de una aplicación móvil basada en la identificación de las plagas (artrópodos) más importantes del cultivo del tomate en España. La aplicación (app) resuelve los problemas a los que se enfrentan agricultores profesionales y aficionados a la hora de identificar plagas, para ello la aplicación guía al usuario siguiendo una sencilla clave dicotómica hasta la identificación. Como valor añadido, la aplicación recomienda posibles tratamientos y medidas a seguir. La app además permite acceder a una página web que recogería información de interés del sector, así como la posibilidad de descargarla. La actualización de la información y el acceso a la web se realiza a través de la comunicación con un servidor web. Con este proyecto se busca facilitar la toma de decisión y minimizar el uso de recursos así como los costes económicos y ambientales. También se intenta contribuir a conseguir una agricultura más verde, responsable y sostenible, uno de los objetivos de la nueva PAC (2014-2020).

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This paper presents a dynamic LM adaptation based on the topic that has been identified on a speech segment. We use LSA and the given topic labels in the training dataset to obtain and use the topic models. We propose a dynamic language model adaptation to improve the recognition performance in "a two stages" AST system. The final stage makes use of the topic identification with two variants: the first on uses just the most probable topic and the other one depends on the relative distances of the topics that have been identified. We perform the adaptation of the LM as a linear interpolation between a background model and topic-based LM. The interpolation weight id dynamically adapted according to different parameters. The proposed method is evaluated on the Spanish partition of the EPPS speech database. We achieved a relative reduction in WER of 11.13% over the baseline system which uses a single blackground LM.

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A new language recognition technique based on the application of the philosophy of the Shifted Delta Coefficients (SDC) to phone log-likelihood ratio features (PLLR) is described. The new methodology allows the incorporation of long-span phonetic information at a frame-by-frame level while dealing with the temporal length of each phone unit. The proposed features are used to train an i-vector based system and tested on the Albayzin LRE 2012 dataset. The results show a relative improvement of 33.3% in Cavg in comparison with different state-of-the-art acoustic i-vector based systems. On the other hand, the integration of parallel phone ASR systems where each one is used to generate multiple PLLR coefficients which are stacked together and then projected into a reduced dimension are also presented. Finally, the paper shows how the incorporation of state information from the phone ASR contributes to provide additional improvements and how the fusion with the other acoustic and phonotactic systems provides an important improvement of 25.8% over the system presented during the competition.

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[Comentario a la muerte de] Don Modesto López Otero

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Manuscrito encuadernado con: Concilia Magnae Britanniae et Hiberniae a Synodo Verolamiensi... (XVIII/68-TG)

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Manuscrito encuadernado con: Concilia Magnae Britanniae et Hiberniae a Synodo Verolamiensi...(XVIII/68-TG)

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This paper proposes an emotion transplantation method capable of modifying a synthetic speech model through the use of CSMAPLR adaptation in order to incorporate emotional information learned from a different speaker model while maintaining the identity of the original speaker as much as possible. The proposed method relies on learning both emotional and speaker identity information by means of their adaptation function from an average voice model, and combining them into a single cascade transform capable of imbuing the desired emotion into the target speaker. This method is then applied to the task of transplanting four emotions (anger, happiness, sadness and surprise) into 3 male speakers and 3 female speakers and evaluated in a number of perceptual tests. The results of the evaluations show how the perceived naturalness for emotional text significantly favors the use of the proposed transplanted emotional speech synthesis when compared to traditional neutral speech synthesis, evidenced by a big increase in the perceived emotional strength of the synthesized utterances at a slight cost in speech quality. A final evaluation with a robotic laboratory assistant application shows how by using emotional speech we can significantly increase the students’ satisfaction with the dialog system, proving how the proposed emotion transplantation system provides benefits in real applications.