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Αναγνώριση χειρονομιών για σύνθεση προτάσεων με πιθανοτικούς αλγόριθμους

Giannelos Evangelos

Πλήρης Εγγραφή

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Περίληψη

The purpose of this work was to develop a standalone system that predictstext and outputs speech synthesis for people with physical disabilities andreduced fine motor function. A low-cost, infrared hand tracking device wasutilized, typically used in virtual/augmented reality applications. The implementedsystem offers two basic functionalities. First, a human-computerinteraction (HCI) functionality that is customizable and offers enough featuresthat can be tailored to a large number of different users. Second, a wayto predict what the user intends to write in order to reduce the user’s inputtext as much as possible, speeding up overall communication. The wordprediction task was mainly based on n-grams (and relevant Markov Chains),abbreviation expansion (and lookup tables) and recurrent neural networks.Evaluation results confirmed that the simple prediction methods utilized acceleratedword typing speed, saving input text by approximately 63%. Futurework could utilize additional eye-tracking or hand-tracking sensors.

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