Real-time Beat Tracking System with Mel-Frequency Cepstral Coefficient Method and ANN for ERISA Dance Robot Motion-Reference-Cited by-同舟云学术

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Real-time Beat Tracking System with Mel-Frequency Cepstral Coefficient Method and ANN for ERISA Dance Robot Motion

Published:2023-08-08 Issue: Volume: Page:
ISSN:
Container-title:2023 International Electronics Symposium (IES)
language:
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Author:

Rohmawati Nur Menik¹,Sudibyo Rahardhita Widyatra¹,Satria Novian Fajar²,Binugroho Eko Henfri²,Basuki Dwi Kurnia³,Santoso Rachmat⁴

Affiliation:

1. Politeknik Elektronika Negeri Surabaya,Electrical Engineering Department,Surabaya,Indonesia

2. Politeknik Elektronika Negeri Surabaya,Mechatronic Engineering Department,Surabaya,Indonesia

3. Politeknik Elektronika Negeri Surabaya,Computer Engineering Department,Surabaya,Indonesia

4. Politeknik Elektronika Negeri Surabaya,Creative Multimedia Technology Department,Surabaya,Indonesia

Funder

Politeknik Elektronika Negeri Surabaya

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10242388/10242392/10242565.pdf?arnumber=10242565

Reference17 articles.

1. An Acoustic Recognition Model for English Speech Based on Improved HMM Algorithm

2. Perbandingan Metode Hidden Markov Model dan Vector Quantization untuk Aplikasi Identifikasi Suara;harry khesa s;Spektrum,2016

3. Cardiac Sound Classification Using Mel-Frequency Cepstral Coefficients (MFCC) and Artificial Neural Network (ANN)

4. Arabic speech recognition using MFCC feature extraction and ANN classification

5. Sistem Automatic Speech Recognition Menggunakan Metode Mfcc Dan Hmms Untuk Deteksi Kesalahan Pengucapan Kata Bahasa Inggris;azizah;eproceedings of engineering,2015

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