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A Hybrid Model for the Prediction of the Linguistic Origin of Surnames
May/June 2003 (vol. 15 no. 3)
pp. 760-763

Abstract—The prediction of the linguistic origin of surnames is a basic functionality required in the design of high-quality multilanguage speech synthesizers. The assignment of a given string representing a surname to a specific language is typically based on a set of rules which can hardly be written in an explicit form. The approach we propose faces this problem combining a rule-based system with a module based on evidential reasoning and a module based on neural networks. The resulting hybrid system combines the different sources of information, merging both knowledge from experts on linguistics and knowledge automatically acquired using learning from examples. The system has been validated on a large database containing surnames belonging to four different languages, showing its effectiveness for real-world applications.

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Index Terms:
Dempster-Shafer's theory, hybrid systems, neural networks, speech synthesizers, surname classification.
Citation:
Patrizia Bonaventura, Marco Gori, Marco Maggini, Franco Scarselli, Jianqing Sheng, "A Hybrid Model for the Prediction of the Linguistic Origin of Surnames," IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 3, pp. 760-763, May-June 2003, doi:10.1109/TKDE.2003.1198404
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