Tessa, a system to aid communication with deaf people
Proceedings of the fifth international ACM conference on Assistive technologies
A systematic comparison of various statistical alignment models
Computational Linguistics
A corpus-centered approach to spoken language translation
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Discriminative training and maximum entropy models for statistical machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Machine Translation with Inferred Stochastic Finite-State Transducers
Computational Linguistics
N-gram-based Machine Translation
Computational Linguistics
Speech to sign language translation system for Spanish
Speech Communication
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
Spoken Spanish generation from sign language
Interacting with Computers
Increasing adaptability of a speech into sign language translation system
Expert Systems with Applications: An International Journal
Methodology for developing an advanced communications system for the Deaf in a new domain
Knowledge-Based Systems
A rule-based translation from written Spanish to Spanish Sign Language glosses
Computer Speech and Language
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This paper describes a preprocessing module for improving the performance of a Spanish into Spanish Sign Language (Lengua de Signos Espanola: LSE) translation system when dealing with sparse training data. This preprocessing module replaces Spanish words with associated tags. The list with Spanish words (vocabulary) and associated tags used by this module is computed automatically considering those signs that show the highest probability of being the translation of every Spanish word. This automatic tag extraction has been compared to a manual strategy achieving almost the same improvement. In this analysis, several alternatives for dealing with non-relevant words have been studied. Non-relevant words are Spanish words not assigned to any sign. The preprocessing module has been incorporated into two well-known statistical translation architectures: a phrase-based system and a Statistical Finite State Transducer (SFST). This system has been developed for a specific application domain: the renewal of Identity Documents and Driver's License. In order to evaluate the system a parallel corpus made up of 4080 Spanish sentences and their LSE translation has been used. The evaluation results revealed a significant performance improvement when including this preprocessing module. In the phrase-based system, the proposed module has given rise to an increase in BLEU (Bilingual Evaluation Understudy) from 73.8% to 81.0% and an increase in the human evaluation score from 0.64 to 0.83. In the case of SFST, BLEU increased from 70.6% to 78.4% and the human evaluation score from 0.65 to 0.82.