IMPLEMENTASI MODEL DETEKSI WAKE WORD UNTUK INTELLIGENT VOICE ASSISTANT MENGGUNAKAN METODE CONVOLUTIONAL RECCURENT NEURAL NETWORK

MULYANA, IKA ELVINA and Ubaya, Huda (2021) IMPLEMENTASI MODEL DETEKSI WAKE WORD UNTUK INTELLIGENT VOICE ASSISTANT MENGGUNAKAN METODE CONVOLUTIONAL RECCURENT NEURAL NETWORK. Undergraduate thesis, Sriwijaya University.

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Abstract

Artificial Intelligence (AI) is a system that regulates human-machine interaction, especially through voice. Intelligent Voice Assistant (IVA) technology is a technology that uses voice to perform commands. There is an important aspect in IVA, namely Wake Word (WW) detection. WW is speech recognition found by word number identification (keyword). Wake Word used is the word "active". The Convolutional Recurrent Neural Network (CRNN) method is a combination of two neural networks involving CNN followed by RNN, by connecting the two CRNN networks to produce good and quite optimal results, especially for audio signals. CRNN has the advantage that in the convolutional layer there is an efficient feature extraction followed by a repeating layer that can extract information from the sequence of features generated by the convolutional layer. With the CRNN model, the results obtained for detecting the "active" sound in this study were an accuracy of 99.37%. Keyword: Artificial Intelligent, Wake Word, Intelligent Voice Assistant, Convolutional Recurrent Neural Network

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Artificial Intelligent, Wake Word, Intelligent voice Assistant, Convolutional Recurrent Neural Network.
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Ms Ika Elvina Mulyana
Date Deposited:	16 Dec 2021 04:28
Last Modified:	16 Dec 2021 04:28
URI:	http://repository.unsri.ac.id/id/eprint/59290

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