基于信号频谱协同分析算法的音乐训练智能平台构建

Mei Liu
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引用次数: 0

摘要

本文简要回顾了几种常见的区分理论及其局限性,并超越音乐本身的范畴,从音乐的频谱特征来分析古典音乐与流行音乐的区别。信号投影图作为一种人机交互界面,可以帮助分析人员直观、交互式地识别信号数量,并对信号特征数据进行聚类。同时,设计了一种新颖的信号流图,可同时显示不同无线电信号模式的多特征时变特性。对采集到的音频信号在算法中进行逆序位和蝴蝶运算优化,然后利用优化后的算法对不同格式的音频信号进行频谱分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction of Music Training Intelligent Platform based on Signal Spectrum Collaborative Analysis Algorithm
This paper briefly reviews several common distinction theories and their limitations, and goes beyond the category of music itself to analyze the difference between classical music and popular music from the spectrum characteristics of music. As a human-computer interaction interface, the signal projection graph helps analysts visually and interactively identify the number of signals and cluster signal feature data. At the same time, a novel signal flow graph is designed to simultaneously display the multi-feature time-varying characteristics of different radio signals Mode. Optimize the reverse order bit and butterfly operation in the algorithm for the collected audio signal, and then use the optimized algorithm to perform spectrum analysis on audio signals in different formats.
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