VOICE RECOGNITION BY NEURAL-NETWORK UNDER TRACTOR NOISE

Experiments were conducted to investigate the possibility of using a n eural network for operator's voice recognition under tractor noise. Th is concept will be used to control some of the tractor's functions by oral commands from the operator. Due to limited capacity of the networ k used, this investigation focused on the recognition of the vowels a, e, i, o, and u. The effect of variation in pitch of input voice and i nput units was investigated. The neural network was initially trained to recognize input voice and noise, and later during recognition, it c ompared the learned signals and test signals to distinguish between th e tractor noise and operator's voice. All investigations were carried out at a fixed tractor noise level at 2500 rev/min of the engine. The effect of variation in sound pressure level was studied. It was observ ed that the neural network can be successfully used to recognize the o perator's voice under the tractor noise. Input units of 256 or 128 wer e sufficient to recognize the steady state vowels used in this study. The sound pressure level affected the misrecognitions.