Classification of Musical Instruments Sound Using Pre-Trained Model with Machine Learning Techniques

S. Prabavathy
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引用次数: 1

Abstract

Classify the musical instruments by machine is a challenging task. Musical data classification becomes very popular in research field. A huge manual process required to classify the musical instrument. This proposed system classifies the musical instruments using GoogleNet which is a pretrained network model; SVM and kNN are the two techniques which is used to classify the features. In this paper, to simply musical instruments classifications based on its features which are extracted from various instruments using recent algorithms. The performance of kNN with SVM compares in this proposed work. The musical instruments are identified and its accuracy is computed with the classifiers SVM and kNN, using the SVM with GoogleNet 99% achieve as a high accuracy rate in classifying the musical instruments. In this system sixteen musical instruments used to find the accuracy using SVM and kNN.
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使用机器学习技术的预训练模型对乐器声音进行分类
用机器对乐器进行分类是一项具有挑战性的任务。音乐数据分类已成为研究领域的热点。对乐器进行分类需要大量的手工操作。该系统使用预训练网络模型GoogleNet对乐器进行分类;SVM和kNN是两种用于特征分类的技术。本文利用最新的算法从各种乐器中提取乐器的特征,对乐器进行简单的分类。本文对kNN与SVM的性能进行了比较。利用支持向量机和kNN分类器对乐器进行识别并计算其准确率,使用支持向量机和GoogleNet对乐器进行分类,准确率达到99%。该系统利用支持向量机和kNN对16种乐器进行精度检测。
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