MLFNN algorithm for speech classification using mmfc feature extraction in a smart wheelchair
Corressponding author's email:
haint@hcmute.edu.vnKeywords:
MMFC feature extraction, Speech classification, Hamming low-pass filter and Multiplayer Neural NetworksAbstract
This paper proposes a Multilayer Feed forward Neural Network (MLFNN) for speech classification in a smart electric wheelchair, in which with extraction of speech commands is performed using a Mel Frequency Cepstral Coefficients (MMFC) method. Speech commands recognized here are Left, Right, Forward, Backward and Stop. In addition, a Hamming low- pass filter is applied to reduce noise before feature extraction. Therefore, the recognized signals will be used to control the electric wheelchair. Results of this study possibly support disabled people using the wheelchair to move easily and more convenient in everyday life and also show to illustrate the effectiveness of the proposed approach.
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