Feature Extraction of Musical Instrument Tones using FFT and Segment Averaging
| Autor: | Iswanjono Iswanjono, Linggo Sumarno |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
business.industry Feature extraction Fast Fourier transform Pattern recognition Musical instrument Signal Domain (software engineering) FFT segment averaging Tone (musical instrument) symbols.namesake Fourier transform symbols Artificial intelligence Electrical and Electronic Engineering business musical instrument tones Left half |
| Popis: | A feature extraction for musical instrument tones that based on a transform domain approach was proposed in this paper. The aim of the proposed feature extraction was to get the lower feature extraction coefficients. In general, the proposed feature extraction was carried out as follow. Firstly, the input signal was transformed using FFT (Fast Fourier Transform). Secondly, the left half of the transformed signal was divided into a number of segments. Finally, the averaging results of that segments, was the feature extraction of the input signal. Based on the test results, the proposed feature extraction was highly efficient for the tones, which have many significant local peaks in the Fourier transform domain, because it only required at least four feature extraction coefficients, in order to represent every tone. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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