Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition
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...
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| Format: | Article |
| Language: | English |
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Universitas Sanata Dharma
2024-12-01
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| Series: | International Journal of Applied Sciences and Smart Technologies |
| Online Access: | https://e-journal.usd.ac.id/safe/index.php/IJASST/article/view/9972 |
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| author | Linggo Sumarno |
| author_facet | Linggo Sumarno |
| author_sort | Linggo Sumarno |
| collection | DOAJ |
| description | 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 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 extraction |
| format | Article |
| id | doaj-art-0ed6ab38de7445049b9f0fa829ff54fb |
| institution | OA Journals |
| issn | 2655-8564 2685-9432 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Universitas Sanata Dharma |
| record_format | Article |
| series | International Journal of Applied Sciences and Smart Technologies |
| spelling | doaj-art-0ed6ab38de7445049b9f0fa829ff54fb2025-08-20T02:32:22ZengUniversitas Sanata DharmaInternational Journal of Applied Sciences and Smart Technologies2655-85642685-94322024-12-016241742810.24071/ijasst.v6i2.99723750Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord RecognitionLinggo Sumarno0Sanata Dharma UniversityThis 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 extractionhttps://e-journal.usd.ac.id/safe/index.php/IJASST/article/view/9972 |
| spellingShingle | Linggo Sumarno Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition International Journal of Applied Sciences and Smart Technologies |
| title | Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition |
| title_full | Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition |
| title_fullStr | Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition |
| title_full_unstemmed | Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition |
| title_short | Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition |
| title_sort | evaluating the performance of dwt dct feature extraction in guitar chord recognition |
| url | https://e-journal.usd.ac.id/safe/index.php/IJASST/article/view/9972 |
| work_keys_str_mv | AT linggosumarno evaluatingtheperformanceofdwtdctfeatureextractioninguitarchordrecognition |