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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/7123ABC9-7723-4E8F-9BB0-61516EDCBA6A | - |
| Identifier | https://doi.org/10.26233/heallink.tuc.78338 | - |
| Language | en | - |
| Extent | 57 pages | en |
| Title | Gesture recognition for sentence synthesis with probabilistic algorithms | en |
| Title | Αναγνώριση χειρονομιών για σύνθεση προτάσεων με πιθανοτικούς αλγόριθμους | el |
| Creator | Giannelos Evangelos | en |
| Creator | Γιαννελος Ευαγγελος | el |
| Contributor [Thesis Supervisor] | Bletsas Aggelos | en |
| Contributor [Thesis Supervisor] | Μπλετσας Αγγελος | el |
| Contributor [Committee Member] | Mania Aikaterini | en |
| Contributor [Committee Member] | Μανια Αικατερινη | el |
| Contributor [Committee Member] | Partsinevelos Panagiotis | en |
| Contributor [Committee Member] | Παρτσινεβελος Παναγιωτης | el |
| Publisher | Πολυτεχνείο Κρήτης | el |
| Publisher | Technical University of Crete | en |
| Academic Unit | Technical University of Crete::School of Electrical and Computer Engineering | en |
| Academic Unit | Πολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών | el |
| Content Summary | The purpose of this work was to develop a standalone system that predicts text and outputs speech synthesis for people with physical disabilities and reduced fine motor function. A low-cost, infrared hand tracking device was utilized, typically used in virtual/augmented reality applications. The implemented system offers two basic functionalities. First, a human-computer interaction (HCI) functionality that is customizable and offers enough features that can be tailored to a large number of different users. Second, a way to predict what the user intends to write in order to reduce the user’s input text as much as possible, speeding up overall communication. The word prediction 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 accelerated word typing speed, saving input text by approximately 63%. Future work could utilize additional eye-tracking or hand-tracking sensors. | en |
| Type of Item | Διπλωματική Εργασία | el |
| Type of Item | Diploma Work | en |
| License | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en |
| Date of Item | 2018-07-13 | - |
| Date of Publication | 2018 | - |
| Subject | Natural Language Processing | en |
| Subject | Human-Computer Interaction | en |
| Subject | Augmented and Alternative Communication | en |
| Bibliographic Citation | 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 | en |
| Bibliographic Citation | Ευάγγελος Γιαννέλος, "Αναγνώριση χειρονομιών για σύνθεση προτάσεων με πιθανοτικούς αλγόριθμους", Διπλωματική Εργασία, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2018 | el |
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