GENDER CLASSIFICATION BASED ON VOICE USING RECURRENT NEURAL NETWORK (RNN)
Abstract
The information technology field continues to progress rapidly. Technological progress is kept in check with such factors as touch, sight, and sound. Each man with another man has a characteristic difference, one that can be seen is by his voice. The processing of sound is an essential concept to all kinds of systems that require human interaction in its daily activities. One of the techniques used in processing speech is classification, which has a direct effect on speech recognition systems. SimpleRNN and LSTM are models of deep learning that can be used to classify sentiment. It can process data in such a sequence as sound, video, and text. These results provide accuracy 90% of the test data and 95% accuracy to the training data.
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References
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