Evangelos Giannelos, "Gesture recognition for sentence synthesis with probabilistic algorithms", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2018
https://doi.org/10.26233/heallink.tuc.78338
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.