Fast robot voice interface through optimum-path forest
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Resumo
Voice-based user interfaces have been actively pursued aiming to help individuals with motor impairments, providing natural interfaces to communicate with machines. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for voice-based robot interface, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster. Experiments were conducted against Support Vector Machines, Neural Networks and a Bayesian classifier to show the OPF robustness. The proposed architecture provides high accuracy rates allied with low computational times. © 2012 IEEE.
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Accuracy rate, Bayesian classifier, Computational time, Machine learning techniques, Motor impairments, Natural interfaces, Optimum-path forests, Pattern recognition techniques, Proposed architectures, Robot interface, Voice interfaces, Learning systems, Pattern recognition, User interfaces, Forestry, Interfaces, Networks, Optimization, Patterns, Robots
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Inglês
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INES 2012 - IEEE 16th International Conference on Intelligent Engineering Systems, Proceedings, p. 67-71.
