Features for Handwriting Recognition
In the following page you could find tools for computing several features for handwriting recognition.
Feature Extraction Tools.
iATROS (Improved ATROS)
iATROS is a new implementation of a previous speech recogniser that has been adapted to be used in both speech and handwritten text recognition. iATROS provides a modular structure that can be used to build different systems whose core is a Viterbi-like search on a Hidden Markov Model network. iATROS provides standard tools for off-line recognition and on-line speech recognition (based on ALSA modules). Download.
- Míriam Luján-Mares, Vicent Tamarit, Vicent Alabau, Carlos-D. Martínez-Hinarejos, Moisés Pastor, Alberto Sanchis, and Alejandro Toselli. iatros: A speech and handwritting recognition system. In V Jornadas en Tecnologías del Habla (VJTH'2008), pages 75-78, Bilbao (SPAIN), Nov 2008
Thot: a toolkit for phrase-based statistical machine translation
Thot is an open source toolkit for statistical machine translation. Originally, Thot incorporated tools to train phrase-based models. The new version of Thot now includes a state-of-the-art phrase-based translation decoder as well as tools to estimate all of the models involved in the translation process. In addition to this, Thot is also able to incrementally update its models in real time after presenting an individual sentence pair. Download
- (Ortiz-Martínez et al. 2014) D. Ortiz-Martínez and F. Casacuberta. The New Thot Toolkit for Fully-Automatic and Interactive Statistical Machine Translation. In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL), pages 45-48, Gothenburg, Sweden, April 2014
iGREAT (interactive GREAT)
iGREAT is an open-source, statistical machine translation software toolkit based on finite-state models. Download
- Jorge González, Francisco Casacuberta. GREAT: open source software for statistical machine translation. Machine translation, 2011. Vol. 25 (2), pp. 145-160.
- J. González and F. Casacuberta. GREAT: a finite-state machine translation toolkit implementing a Grammatical Inference Approach for Transducer Inference (GIATI). In EACL Workshop on Computational Linguistics Aspects of Grammatical Inference, pages 24-32, Athens, Greece, March 30 2009.
- J. González, G. Sanchis, and F. Casacuberta. Learning finite state transducers using bilingual phrases. In 9th International Conference on Intelligent Text Processing and Computational Linguistics. Lecture Notes in Computer Science, Haifa, Israel, February 17 to 23 2008.
jaf MT: A phrased-based hidden semi-Markov Model for SMT
jaf MT is sowftware for training phrased-based hidden semi-Markov Model for SMT. Download.
- Jesús Andrés-Ferrer, Alfons Juan.. A phrase-based hidden semi-Markov approach to machine translation. Procedings of European Association for Machine Translation (EAMT), 2009. pp. 168-175.