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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA
Hilman Ferdinandus Pardede
Lembaga Ilmu Pengetahuan Indonesia, Bandung
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Klasifikasi Dialek Pengujar Bahasa Inggris Menggunakan Random Forest Muhamad Azhar; Hilman Ferdinandus Pardede
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2754

Abstract

Speech recognition is one of the important research fields which is currently widely used for various applications. However, speech recognition performance is affected by the dialect of the speaker. Therefore, dialect recognition is often used as an additional feature in speech recognition. The process of recognizing dialects is not easy. Currently, Machine Learning technology is widely applied in dialect recognition. One of the challenges in the introduction of machine learning-based dialects is the imbalance of classes and overlaps in a wide variety of classification techniques. This study applies Random Forest-based oversampling technology for dialect recognition. For hyper-parameter optimization of the random forest algorithm, we apply the Grid Search method. Experiments on Speech Accent Archive data using the MFCC feature resulted in an accuracy of 0.91 and AUC of 0.95
Co-Authors Muhamad Azhar