Iranzo Sánchez, Javier(Universitat Politècnica de València, 2018-09-11)
[EN] Machine Translation (MT) is one of the most active areas in Artificial Intelligence,
particularly in Pattern Recognition. MT has recently received a great deal of attention
by key technology players such as Google, ...
Ciscar Martinez, Vicent Andreu(Universitat Politècnica de València, 2019-01-14)
La Educación Abierta se ha convertido en una aproximación revolucionaria para el futuro de la educación permitiendo el acceso mundial a un gran volumen de Recursos Educativos Abiertos (REA). Un ejemplo emblemático de REA ...
Silvestre Cerdà, Joan Albert; Giménez Pastor, Adrián; Andrés Ferrer, Jesús; Civera Saiz, Jorge; Juan Císcar, Alfonso(Ramos Castro, Daniel, 2012-11-21)
This paper describes the audio segmentation system developed
by the PRHLT research group at the UPV for the Albayzin Audio
Segmentation Evaluation 2012. The PRHLT-UPV audio segmentation
system is based on a conventional ...
[EN] Hidden Markov Models (HMMs) are now widely used for off-line text recognition in many languages and, in particular, Arabic. In previous work, we proposed to directly use columns of raw, binary image pixels, which are ...
This paper presents a handwritten word recogniser based on HMMs at subword level (characters) in which state-emission probabilities are governed by multivariate Bernoulli probability functions. This recogniser works directly ...
Giménez Pastor, Adrián(Universitat Politècnica de València, 2014-06-09)
In last years Hidden Markov Models (HMMs) have received significant attention in the
task off-line handwritten text recognition (HTR). As in automatic speech recognition (ASR),
HMMs are used to model the probability of ...
Doetsch, Patrick; Hamdani, Mahdi; Ney, Hermann; Giménez Pastor, Adrián; Andrés Ferrer, Jesús; Juan Císcar, Alfonso(Institute of Electrical and Electronics Engineers (IEEE), 2012-09-18)
—In this paper a vertical repositioning method
based on the center of gravity is investigated for handwriting
recognition systems and evaluated on databases containing
Arabic and French handwriting. Experiments show ...
Wuebker, Joern; Ney, Hermann; Martínez-Villaronga, Adrià; Giménez Pastor, Adrián; Juan Císcar, Alfonso; Servan, Christophe; Dymetman, Marc; Mirkin, Shashar(Association for Machine Translation in the Americas, 2014-10-22)
[EN] For the task of online translation of scientific video lectures, using huge models is not possible.
In order to get smaller and efficient models, we perform data selection. In this paper, we
perform a qualitative ...
Roselló Beneitez, Nahuel Unai(Universitat Politècnica de València, 2021-10-14)
[ES] El Reconocimiento Automático del Habla (RAH) ha demostrado ser una manera efectiva y eficiente de convertir habla a texto a lo largo de los últimos años. Este trabajo, desarrollado en el contexto de dos proyectos ...
Iranzo-Sánchez, Javier; Giménez Pastor, Adrián; Silvestre Cerdà, Joan Albert; Baquero-Arnal, Pau; Civera Saiz, Jorge; Juan, Alfons(Association for Computational Linguistics, 2020-11-20)
[EN] The cascade approach to Speech Translation
(ST) is based on a pipeline that concatenates
an Automatic Speech Recognition (ASR) system followed by a Machine Translation (MT)
system. These systems are usually connected
by ...
[EN] Bernoulli HMMs (BHMMs) have been successfully applied to handwritten text recognition (HTR) tasks such as continuous and isolated handwritten words. BHMMs belong to the generative model family and, hence, are usually ...
Giménez Pastor, Adrián; Andrés Ferrer, Jesús; Juan Císcar, Alfonso; Serrano Martinez Santos, Nicolas(Institute of Electrical and Electronics Engineers (IEEE), 2011-09-18)
Bernoulli-based models such as Bernoulli mixtures
or Bernoulli HMMs (BHMMs), have been successfully applied
to several handwritten text recognition (HTR) tasks which
range from character recognition to continuous and ...
[EN] Hidden Markov Models (HMMs) are now widely used for off-line handwriting recognition in many lan-
guages. As in speech recognition, they are usually built from shared, embedded HMMs at symbol level,
where state-conditional ...
Serrano Martinez Santos, Nicolas; Giménez Pastor, Adrián; Civera Saiz, Jorge; Sanchis Navarro, José Alberto; Juan Císcar, Alfonso(Springer Verlag (Germany), 2014-03-01)
[EN] Transcription of handwritten text in (old) documents is an important, time-consuming task for digital libraries. Although post-editing automatic recognition of handwritten text is feasible, it is not clearly better ...
This paper shows how the nowadays prevalent technology used in HTR borrows concepts and methods from the field of ASR; i.e. those based on Hidden Markov Models (HMMs). Additionally, it will be described a HTR approach based ...
Jorge-Cano, Javier; Giménez Pastor, Adrián; Silvestre Cerdà, Joan Albert; Civera Saiz, Jorge; Sanchis Navarro, José Alberto; Juan, Alfons(Institute of Electrical and Electronics Engineers, 2022)
[EN] Although Long-Short Term Memory (LSTM) networks and deep Transformers are now extensively used in offline ASR, it is unclear how best offline systems can be adapted to work with them under the streaming setup. After ...
Iranzo Sánchez, Javier(Universitat Politècnica de València, 2019-10-30)
[ES] La traducción automática (MT) es un área de investigación sobre el desarrollo de sistemas que traducen textos de manera automática. Actualmente, la mayoría de sistemas de MT utilizan redes neuronales en lo que se ...
Giménez Pastor, Adrián(Universitat Politècnica de València, 2011-10-18)
En este trabajo presentamos un sistema de reconocimiento de palabras manuscritas
basado en HMMs segmentados con mixturas de Bernoulli en los estados. Este sistema es
aplicado al corpus IAM y comparado con otro, basado ...
Del Agua Teba, Miguel Angel; Giménez Pastor, Adrián; Sanchis Navarro, José Alberto; Civera Saiz, Jorge; Juan, Alfons(Institute of Electrical and Electronics Engineers, 2018)
[EN] In the last years, Deep Bidirectional Recurrent Neural Networks (DBRNN) and DBRNN with Long Short-Term Memory cells (DBLSTM) have outperformed the most accurate classifiers for confidence estimation in automatic speech ...