IMPLEMENTASI MODEL REKOGNISI SUARA MENGGUNAKAN METODE CONVOLUTIONAL RECURRENT NEUTAL NETWORK (CRNN)

OCTAVYA, NANDA HARSANA and Ubaya, Huda (2021) IMPLEMENTASI MODEL REKOGNISI SUARA MENGGUNAKAN METODE CONVOLUTIONAL RECURRENT NEUTAL NETWORK (CRNN). Undergraduate thesis, Sriwijaya University.

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Abstract

Voice recognition is a process that can determine the identity of the user based on the characteristics of the voice through the words conveyed because every human being has a distinctive sound characteristic. Human voices can be recognized by gender. Recognition of gender or gender based on voice can be detected automatically through the characteristics of the voice. The method used in this research is Convolutional Recurrent Neural Network (CRNN). Based on the tuning process that has been carried out, the parameter values that produce the best output are the distribution of 80% training data and 20% testing data, batch_size of 8, learning-rate of 0.0001 and epoch of 300. The model that has been built produces a Training Accuracy value of 99 ,41% while Testing Accuracy is 99.05%. The average training performance value obtained from each class is 99.3% for the value of Specificity, Precision and Recall, while the FI-Score value is 99.4%. The average Testing performance value obtained from each class is 98.9% for the Specifity, Precision and Recall values, while the FI-Score value is 99%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Rekognisi, Suara, Gender, Convolutional Recurrent Neural Network.
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Nanda Harsana Octavya
Date Deposited:	29 Jul 2021 07:57
Last Modified:	29 Jul 2021 07:57
URI:	http://repository.unsri.ac.id/id/eprint/51006

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