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All Journal Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC)
Akhmad Anggoro
Universitas Gadjah Mada
Aerospace Engineering Computer Science & IT Electrical & Electronics Engineering Engineering

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MFCC dan KNN untuk Pengenalan Suara Artikulasi P Akhmad Anggoro; Samiadji Herdjunanto; Risanuri Hidayat
Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Vol 2, No 1 (2020): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v2i1.605

Abstract

Cleft lip and palate (CLP) is a term for patients who experience speech organ disorders, that disorder is caused by a gap found in the lip or palate. Patients will experience speech problems. Pattern recognition in CLP sound is still small in Indonesia. In this research in the language identification of CLP and standard sound patterns using the extraction of the Mel Frequency Cepstral Coefficients (MFCC) feature with K-Nearest Neighbor (KNN) classification and K-Fold cross-validation. By making words that have the letter /p/ as a reference, known as bilabial. The words used include Paku, Kapak, and Atap. The accuracy of recognition results reached more than 69%, with a minimum accuracy of 41%.
Co-Authors Risanuri Hidayat Samiadji Herdjunanto