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Penanganan Noise pada Model Klasifikasi Perintah Suara Menggunakan Complete EEMD with Adaptive Noise (CEEMDAN) / Resya Firmansyah

Detail koleksi

Penanganan Noise pada Model Klasifikasi Perintah Suara Menggunakan Complete EEMD with Adaptive Noise (CEEMDAN) / Resya Firmansyah

Pengarang
Firmansyah, Resya Buono, Agus (Pembimbing I) Hardhienata, Medria Kusuma Dewi (Pembimbing II)
Jenis bahan
Tesis
Edisi
-
Penerbitan
Bogor : IPB University, 2022
Deskripsi fisik
xi, 49 halaman : Ilustrasi ; 29 cm.
Bahasa
Indonesia
ISBN / ISSN / ISMN
-
Subjek
Matematika & Ilmu Pengetahuan Alam-- Ilmu Komputer * Computer Science-- Computer Programs-- 2022-- Bogor - Jawa Barat
Abstrak
The application of voice recognition systems is currently widely used in various fields, one of which is voice commands classification. Voice classification is basically done by using feature extraction to recognize the characteristics of each signal. The MFCC method is used in this study. MFCC is a feature extraction method that calculates the cepstral coefficient by imitating the human hearing systems. In this study, the LSTM model with a bidirectional scheme (Bi-LSTM) is used to build a voice command classification model. This method is considered to be able to accommodate the characteristics of voice commands which have a short duration and sensitive to noise. In order for the classification model to maintain high accuracy, CEEMDAN is used as a noise reduction method. CEEMDAN is considered capable of decomposing noisy signals and separating the original signal from its noise component. The results showed that the Bi-LSTM model had an accuracy of 96% and an F1-score of 95%, but experienced a significant de
Catatan
Tesis (Magister). -- IPB University, 2022
Akses online
http://repository.ipb.ac.id/handle/123456789/115872
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