Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition

Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition

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This study presents advancements in audio signal processing techniques, specifically in enhancing the efficiency of guitar chord recognition.It is a continuation of the previous studies, which also aim at minimizing the feature extraction length with the intended performance.This study adopted two signal processing techniques that are Myo-Inositol common: Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) for use in the feature extraction method.By conducting a systematic evaluation of two key parameters: frame blocking length and wavelet RC046 filter selection, a significant achievement could be achieved.The recognition system managed to obtain chord recognition with an accuracy of up to 91.

43%, by using a feature extraction length of only three, which brought about smaller representation than the previous studies.The outcome of this study will help improve the data processing, which can be applied in real time, in this case in Field Programmable Gate Array (FPGA)-based chord recognition systems.Keywords: chord recognition, Discrete Wavelet Transform, Discrete Cosine Transform, feature extraction.