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All Journal Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen
Abdul Halim Anshor
Teknik Informatika, Universitas Pelita Bangsa
Computer Science & IT Decision Sciences, Operations Research & Management

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Pengembangan Model Prediksi Speech Recognition dengan Algoritma Deep Learning Convolutional Neural Network Abdul Halim Anshor; Aswan Supriyadi Sunge
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 16 No 1 (2026): Maret 2026
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v16i1.1020

Abstract

This study examines the development of an automatic speech recognition (ASR) system in Sundanese, which still faces data limitations. Dialect variations and the lack of labeled data are the main challenges in the speech recognition process. The approach used is a Convolutional Neural Network (CNN) with Mel-Frequency Cepstral Coefficients (MFCC) feature extraction. The data used were 100 voice recordings consisting of West Sundanese and South Sundanese dialects. The processing process was carried out through the stages of pre-emphasis, framing, windowing, Fourier transform, Mel filter bank, and Discrete Cosine Transform to obtain voice features. The data was divided into 80% training data and 20% test data. The CNN model was then trained to recognize the voice patterns of each dialect. Based on the test results, the model achieved an accuracy of 70% with a loss value of 0.60. These results indicate that the approach used can be applied to limited data, although its performance can still be improved in further research.
Co-Authors Aswan Supriyadi Sunge