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Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition
Get PDFThis 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 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 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 extractio
Penjendelaan Gaussian pada Ekstraksi Ciri Perataan Segmen berbasis DST pada Pengenalan Nada Alat Musik
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Generating a Combination of Backpropagation Neural Networks by Means of Random Seeds Evaluation
Get PDFPengaruh Koreksi Ketebalan Huruf Pada Pengenalan Huruf Tulisan Tangan Berbasis Ekstraksi Ciri Pengaburan dan Perataan Blok yang Menggunakan Tapis Gaussian 2D
Get PDFPengenalan Huruf Tulisan Tangan Berderau dan Terskala Berbasis Ekstraksi Ciri DCT dengan Menggunakan Jaringan Syaraf Probabilistik
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