Fast robot voice interface through optimum-path forest - Nakamura, R. [UNESP]; Pereira, L. [UNESP]; Silva, D. [UNESP]; Cardozo, P. [UNESP]; Pereira, C. [UNESP]; Ferasoli, H. [UNESP]; Alves, S. [UNESP]; Pires, R. [UNESP]; Spadotto, A. [UNESP]; Papa, J. [UNESP] (Institute of Electrical and Electronics Engineers (IEEE), 2012)
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.
Keywords: 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