Efficient linguistic prediction for AAC aids is a fundamental issue to increase and improve the communication capabilities of verbal disable people. However, although a number of works describing requirements for prediction engines in AAC languages exists, their adaptability to the specific needs of the user is lacking in literature. In this paper, we describe preliminary techniques for the adaptation of the AAC language model to the peculiar characteristics of the user. More precisely, we describe an automatic procedure able to produce a semantic/statistic linguistic model of the user language behavior given the overall AAC language model, the user dictionary, and a corpus of sentences produced by the user.

User Linguistic Model Adaptivity for Prediction in AAC Message Composition

GATTI, NICOLA;MATTEUCCI, MATTEO;SBATTELLA, LICIA
2005

Abstract

Efficient linguistic prediction for AAC aids is a fundamental issue to increase and improve the communication capabilities of verbal disable people. However, although a number of works describing requirements for prediction engines in AAC languages exists, their adaptability to the specific needs of the user is lacking in literature. In this paper, we describe preliminary techniques for the adaptation of the AAC language model to the peculiar characteristics of the user. More precisely, we describe an automatic procedure able to produce a semantic/statistic linguistic model of the user language behavior given the overall AAC language model, the user dictionary, and a corpus of sentences produced by the user.
0805858075
INF; NLP; AAC; Prediction
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/271976
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