Good Morning to Good Night Greeting Classification Using Mel Frequency Cepstral Coefficient (MFCC) Feature Extraction and Frame Feature Selection

• Main Author: Heriyanto Heriyanto
• Format: Article
• Language: Indonesian
• Published: Universitas Pembangunan Nasional "Veteran" Yogyakarta 2021-03-01
• Series: Telematika
• Subjects: extraction of features; features; frames; cepstral coefficient; linear
• Online Access: http://jurnal.upnyk.ac.id/index.php/telematika/article/view/4495
• ISSN: 1829-667X; 2460-9021

Purpose: Select the right features on the frame for good accuracyDesign/methodology/approach: Extraction of Mel Frequency Cepstral Coefficient (MFCC) Features and Selection of Dominant Weight Normalized (DWN) FeaturesFindings/result: The accuracy results show that the MFCC method with the 9th frame selection has a higher accuracy rate of 85% compared to other frames.Originality/value/state of the art: Selection of the appropriate features on the frame.