Abstract
Encouragingly accurate translations have recently been obtained using a connectionist translator called RECONTRA (Recurrent Connectionist Translator). In contrast to traditional Knowledge-Based systems, this model is built from training data resulting in an Example-Based approach. It directly carries out the translation between the source and target language and employs a simple (recurrent) connectionist topology and a simple training scheme. This paper extends previous work exploring the capabilities of this RECONTRA model to perform text-to-text translations in limited-domain tasks.
Partially supported by the Spanish CICYT, project TIC-97-0745-CO2-02.
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Castano, M.A., Casacuberta, F. (1999). Text-to-text machine translation using the RECONTRA connectionist model. In: Mira, J., Sánchez-Andrés, J.V. (eds) Engineering Applications of Bio-Inspired Artificial Neural Networks. IWANN 1999. Lecture Notes in Computer Science, vol 1607. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0100536
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DOI: https://doi.org/10.1007/BFb0100536
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