Abstract

Automatic speech recognition is the ability to receive and identify spoken words by converting analog signals to digital and extracting unique vocal characteristics such as pitch, frequency, tone, and rhythm to form speaker models or sound samples. The voice sample used is the voice register, the voice register is the division of the area of the human voice based on the source of the sound, the sensation of the resonant space, shape, color, sound timbre, and the high and low tone produced. Discrete Hartley Transform is used as a transformation to process the sound sample to be classified. DHT, DHT + High Pass Filter and DHT + Low Pass Filter in transforming voice register signals can only classify with an average true positive rate of 69.67%. The addition of the filter does not affect the classification results because the sound frequency used is in ideal conditions so that there is no noise that affects the classification results of the voice register.

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