Machine translation based on neural network language models

Este trabajo describe un sistema de traducción que integra n-gramas conexionistas en la etapa de decodificación, motivado por los buenos resultados obtenidos en los últimos años usando estos modelos de lenguaje. Hasta el momento todos los resultados publicados delegan el modelo de lenguaje conexionista a una segunda etapa desacoplada en la que se repuntúan listas de N-best o bien se utilizan sobre grafos de palabras que contienen las N-best. Nuestro objetivo es mostrar la viabilidad de utilizar estos modelos de lenguaje dentro de un sistema totalmente acoplado.This paper describes a Machine Translation system that integrates a Neural Network Language Model in the decoding process. This work is motivated by the excellent performance of these connectionist language models. So far, the use of Neural Network Language Models in the translation systems is uncoupled: they are used in a second stage to rerank a N-best hypothesis list or to parse a word graph containing the N-best list. Our goal is to show the feasibility of using these language models within a fully integrated system

Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System

[EN] Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on n-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and N-gram-based systems, showing that the integrated approach seems more promising for N-gram-based systems, even with nonfull-quality NNLMs.This work was partially supported by the Spanish MINECO and FEDER found under project TIN2017-85854-C4-2-R.Zamora Martínez, FJ.; Castro-Bleda, MJ. (2018). Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System. International Journal of Neural Systems. 28(9). https://doi.org/10.1142/S0129065718500077S28

Autoestima colectiva y aculturación en inmigrantes ecuatorianos

Este estudio examina la relación entre la autoestima colectiva étnica y diferentes aspectos del proceso de aculturación en inmigrantes ecuatorianos residentes en Murcia. De acuerdo con el modelo bidimensional de aculturación, se prueba la hipótesis de la independencia entre el deseo de contacto con el exogrupo y el deseo de mantener el modelo cultural propio. Los resultados señalan que las mujeres quieren mantener su cultura más que los hombres y éstos comportarse como los españoles. Asimismo, se observa que la edad y el nivel de estudios influyen sobre la autoestima privada, el contacto con ecuatorianos y la distancia cultural percibida. Los resultados se comentan con relación a la tradición de investigación de género e inmigración y al modelo bicultural de aculturación.This study examined the relationship between the ethnic collective self-esteem and the process of Ecuadorian immigrants’ acculturation in Murcia (Spain). In accordance with the bidimensional model of acculturation, the hypothesis of the independence between the contact with the outgroup and maintenance of the own ethnic identity is proven. This hypothesis obtains a partial confirmation. The results show that the women want to maintain their culture more than men and these to behave as the Spaniards. Also, it is observed that the age and the level of studies influence on the private self-esteem, the contact with Ecuadorian and the perceived cultural distance. The results are discussed in relation to gender immigration studies and the bicultural model

The NoisyOffice Database: A Corpus To Train Supervised Machine Learning Filters For Image Processing

[EN] This paper presents the `NoisyOffice¿ database. It consists of images of printed text documents with noise mainly caused by uncleanliness from a generic office, such as coffee stains and footprints on documents or folded and wrinkled sheets with degraded printed text. This corpus is intended to train and evaluate supervised learning methods for cleaning, binarization and enhancement of noisy images of grayscale text documents. As an example, several experiments of image enhancement and binarization are presented by using deep learning techniques. Also, double-resolution images are also provided for testing super-resolution methods. The corpus is freely available at UCI Machine Learning Repository. Finally, a challenge organized by Kaggle Inc. to denoise images, using the database, is described in order to show its suitability for benchmarking of image processing systems.This research was undertaken as part of the project TIN2017-85854-C4-2-R, jointly funded by the Spanish MINECO and FEDER founds.Castro-Bleda, MJ.; España Boquera, S.; Pastor Pellicer, J.; Zamora Martínez, FJ. (2020). The NoisyOffice Database: A Corpus To Train Supervised Machine Learning Filters For Image Processing. The Computer Journal. 63(11):1658-1667. https://doi.org/10.1093/comjnl/bxz098S165816676311Bozinovic, R. M., & Srihari, S. N. (1989). Off-line cursive script word recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(1), 68-83. doi:10.1109/34.23114Plamondon, R., & Srihari, S. N. (2000). Online and off-line handwriting recognition: a comprehensive survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(1), 63-84. doi:10.1109/34.824821Vinciarelli, A. (2002). A survey on off-line Cursive Word Recognition. Pattern Recognition, 35(7), 1433-1446. doi:10.1016/s0031-3203(01)00129-7Impedovo, S. (2014). More than twenty years of advancements on Frontiers in handwriting recognition. Pattern Recognition, 47(3), 916-928. doi:10.1016/j.patcog.2013.05.027Baird, H. S. (2007). The State of the Art of Document Image Degradation Modelling. Advances in Pattern Recognition, 261-279. doi:10.1007/978-1-84628-726-8_12Egmont-Petersen, M., de Ridder, D., & Handels, H. (2002). Image processing with neural networks—a review. Pattern Recognition, 35(10), 2279-2301. doi:10.1016/s0031-3203(01)00178-9Marinai, S., Gori, M., & Soda, G. (2005). Artificial neural networks for document analysis and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(1), 23-35. doi:10.1109/tpami.2005.4Rehman, A., & Saba, T. (2012). Neural networks for document image preprocessing: state of the art. Artificial Intelligence Review, 42(2), 253-273. doi:10.1007/s10462-012-9337-zLazzara, G., & Géraud, T. (2013). Efficient multiscale Sauvola’s binarization. International Journal on Document Analysis and Recognition (IJDAR), 17(2), 105-123. doi:10.1007/s10032-013-0209-0Fischer, A., Indermühle, E., Bunke, H., Viehhauser, G., & Stolz, M. (2010). Ground truth creation for handwriting recognition in historical documents. Proceedings of the 8th IAPR International Workshop on Document Analysis Systems - DAS ’10. doi:10.1145/1815330.1815331Belhedi, A., & Marcotegui, B. (2016). Adaptive scene‐text binarisation on images captured by smartphones. IET Image Processing, 10(7), 515-523. doi:10.1049/iet-ipr.2015.0695Kieu, V. C., Visani, M., Journet, N., Mullot, R., & Domenger, J. P. (2013). An efficient parametrization of character degradation model for semi-synthetic image generation. Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing - HIP ’13. doi:10.1145/2501115.2501127Fischer, A., Visani, M., Kieu, V. C., & Suen, C. Y. (2013). Generation of learning samples for historical handwriting recognition using image degradation. Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing - HIP ’13. doi:10.1145/2501115.2501123Journet, N., Visani, M., Mansencal, B., Van-Cuong, K., & Billy, A. (2017). DocCreator: A New Software for Creating Synthetic Ground-Truthed Document Images. Journal of Imaging, 3(4), 62. doi:10.3390/jimaging3040062Walker, D., Lund, W., & Ringger, E. (2012). A synthetic document image dataset for developing and evaluating historical document processing methods. Document Recognition and Retrieval XIX. doi:10.1117/12.912203Dong, C., Loy, C. C., He, K., & Tang, X. (2016). Image Super-Resolution Using Deep Convolutional Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2), 295-307. doi:10.1109/tpami.2015.2439281Suzuki, K., Horiba, I., & Sugie, N. (2003). Neural edge enhancer for supervised edge enhancement from noisy images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(12), 1582-1596. doi:10.1109/tpami.2003.1251151Hidalgo, J. L., España, S., Castro, M. J., & Pérez, J. A. (2005). Enhancement and Cleaning of Handwritten Data by Using Neural Networks. Lecture Notes in Computer Science, 376-383. doi:10.1007/11492429_46Pastor-Pellicer, J., España-Boquera, S., Zamora-Martínez, F., Afzal, M. Z., & Castro-Bleda, M. J. (2015). Insights on the Use of Convolutional Neural Networks for Document Image Binarization. Lecture Notes in Computer Science, 115-126. doi:10.1007/978-3-319-19222-2_10España-Boquera, S., Zamora-Martínez, F., Castro-Bleda, M. J., & Gorbe-Moya, J. (s. f.). Efficient BP Algorithms for General Feedforward Neural Networks. Lecture Notes in Computer Science, 327-336. doi:10.1007/978-3-540-73053-8_33Zamora-Martínez, F., España-Boquera, S., & Castro-Bleda, M. J. (s. f.). Behaviour-Based Clustering of Neural Networks Applied to Document Enhancement. Lecture Notes in Computer Science, 144-151. doi:10.1007/978-3-540-73007-1_18Graves, A., Fernández, S., & Schmidhuber, J. (2007). Multi-dimensional Recurrent Neural Networks. Artificial Neural Networks – ICANN 2007, 549-558. doi:10.1007/978-3-540-74690-4_56Sauvola, J., & Pietikäinen, M. (2000). Adaptive document image binarization. Pattern Recognition, 33(2), 225-236. doi:10.1016/s0031-3203(99)00055-2Pastor-Pellicer, J., Castro-Bleda, M. J., & Adelantado-Torres, J. L. (2015). esCam: A Mobile Application to Capture and Enhance Text Images. Lecture Notes in Computer Science, 601-604. doi:10.1007/978-3-319-19222-2_5

Estudi de l’abandonament en el primer curs de la titulació de telecomunicacions

Dins de la tasca de coordinació del primer curs del grau de telecomunicacions s'ha observat un grau molt elevat d'abandonament de la titulació. Aquest fet condiciona la tasca i metodologia docent. Amb la intenció d'incrementar la qualitat del nou grau i augmentar les taxes de eficàcia, hem buscat els motius que originen aquest alt grau d’abandonament dins la titulació i hem ideat possibles solucions que posen remei o pal·lien en certa mesura aquest problema. Per això es presenten estratègies i mecanismes per augmentar la qualitat de la docència, es comparen els resultats dels darrers cursos i s’analitzen els resultats de les estratègies posades en marxa. La tasca ha estat desenvolupada pels coordinadors de cada assignatura que conjuntament han analitzat com es va produir l'abandó durant l'avaluació continuada.Aquesta comunicació s’ha pogut realitzar gràcies als projectes: GITE-09006-UA i GITE-09014-U

Analysis of holographic data storage using a PA-LCoS device

Holographic data storage systems (HDSS) have been a promising and very appealing technology since the first laser developments in the sixties. Impact of ongoing advances in the various components needs to be explored in its specific application to HDSS. In this sense, continuous progress is being produced in spatial light modulator (SLM) technology where parallel-addressed liquid crystal on silicon (PA-LCoS) microdisplays have replaced previous liquid-crystal displays (LCD) in most of optics and photonics applications. PA-LCoS microdisplays are well adapted to display phaseonly elements without coupled amplitude. In this paper, we analyse how PA-LCoS devices can also be used to display the widely applied binary intensity modulated (BIM) data pages. We also investigate hybrid-ternary modulated (HTM) data pages, which are very much demanding on the phase and amplitude modulation properties of an SLM. HTM data pages combine the ease of detection of BIM data pages, together with a large reduction of the DC term of the Fourier Transform of the data page. This reduction is necessary to avoid saturation of the recording material dynamic range. Simulated results show the magnitude of the expected DC term in the Fourier plane. We have verified the good performance of PA-LCoS to display BIM data pages. We have also obtained that pure HTM data pages cannot be produced with PA-LCoS devices, however, a rather close performance is obtained when implementing the pseudo-HTM data pages. In this work a more complete study of pseudo-HTM modulation is offered.This work was supported by the “Ministerio de Economía y Competitividad” (projects FIS2014-56100-C2-1-P and FIS2015-66570-P) and by the “Generalitat Valenciana” of Spain (projects PROMETEOII/2015/015 and ISIC/2012/013)

Efficient split eld FDTD analysis of third-order nonlinear materials in two-dimensionally periodic media

In this work the split-field finite-difference time-domain method (SF-FDTD) has been extended for the analysis of two-dimensionally periodic structures with third-order nonlinear media. The accuracy of the method is verified by comparisons with the nonlinear Fourier Modal Method (FMM). Once the formalism has been validated, examples of one- and two-dimensional nonlinear gratings are analysed. Regarding the 2D case, the shifting in resonant waveguides is corroborated. Here, not only the scalar Kerr effect is considered, the tensorial nature of the third-order nonlinear susceptibility is also included. The consideration of nonlinear materials in this kind of devices permits to design tunable devices such as variable band filters. However, the third-order nonlinear susceptibility is usually small and high intensities are needed in order to trigger the nonlinear effect. Here, a one-dimensional CBG is analysed in both linear and nonlinear regime and the shifting of the resonance peaks in both TE and TM are achieved numerically. The application of a numerical method based on the finite- difference time-domain method permits to analyse this issue from the time domain, thus bistability curves are also computed by means of the numerical method. These curves show how the nonlinear effect modifies the properties of the structure as a function of variable input pump field. When taking the nonlinear behaviour into account, the estimation of the electric field components becomes more challenging. In this paper, we present a set of acceleration strategies based on parallel software and hardware solutions.This work was supported by the Ministerio de Economa y Competitividad of Spain under project FIS2014-56100- C2-1-P and by the Generalitat Valenciana of Spain under projects PROMETEOII/2015/015, ISIC/2012/013 and GV/2014/076

Acceleration of split-field finite difference time-domain method for anisotropic media by means of graphics processing unit computing

The implementation of split-field finite difference time domain (SF-FDTD) applied to light-wave propagation through periodic media with arbitrary anisotropy method in graphics processing units (GPUs) is described. The SF-FDTD technique and the periodic boundary condition allow the consideration of a single period of the structure reducing the simulation grid. Nevertheless, the analysis of the anisotropic media implies considering all the electromagnetic field components and the use of complex notation. These aspects reduce the computational efficiency of the numerical method compared with the isotropic and nonperiodic implementation. Specifically, the implementation of the SF-FDTD in the Kepler family of GPUs of NVIDIA is presented. An analysis of the performance of this implementation is done, and several applications have been considered in order to estimate the possibilities provided by both the formalism and the implementation into GPU: binary phase gratings and twisted-nematic liquid crystal cells. Regarding the analysis of binary phase gratings, the validity of the scalar diffraction theory is evaluated by the comparison of the diffraction efficiencies predicted by SF-FDTD. The analysis for the second order of diffraction is extended, which is considered as a reference for the transmittance obtained by the SF-FDTD scheme for periodic media.This work was supported by the Ministerio de Economía y Competitividad of Spain under projects FIS2011-29803-C02-01 and FIS2011-29803-C02-02 and by the Generalitat Valenciana of Spain under projects PROMETEO/2011/021, ISIC/2012/013, and GV/2012/099