Musical Instrument Identification with Salient Feature Extraction
Date Issued
2004
Date
2004
Author(s)
Ho, Chyi-Feng
DOI
en-US
Abstract
Music content analysis usually has many practical applications. For example, such applications include database retrieval systems, automatic music signal annotation, and musicians’ tools. In this thesis, we present a system for musical instrument classification. A wide set of features covering both spectral and temporal properties are investigated and their extraction algorithms are designed. We apply the K-Nearest Neighbors algorithm as the classification method. The instrument samples included string (bowed and struck), woodwind (single, double, and air reed). Using the complete feature for training, we achieve a perfect accuracy. We apply decision trees to select the best feature subset to improve the identification performance.
Subjects
DFT
K-Nearest Neighbors
特徵值
樂器音色分類
feature extraction
instrument classification
Type
thesis
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