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Polyphonic Audio Key Finding Using the Spiral Array CEG Algorithm

机译:使用螺旋阵列CEG算法的复音音频键查找

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Key finding is an integral step in content-based music indexing and retrieval. In this paper, we present an O(n) real-time algorithm for determining key from polyphonic audio. We use the standard Fast Fourier Transform with a local maximum detection scheme to extract pitches and pitch strengths from polyphonic audio. Next, we use Chew's Spiral Array Center of Effect Generator (CEG) algorithm to determine the key from pitch strength information. We test the proposed system using Mozart's Symphonies. The test data is audio generated from MIDI source. The algorithm achieves a maximum correct key recognition rate of 96% within the first fifteen seconds, and exceeds 90% within the first three seconds. Starting from the extracted pitch strength information, we compare the CEG algorithm's performance to the classic Krumhansl-Schmuckler (K-S) probe tone profile method and Temperley's modified version of the K-S method. Correct key recognition rates for the K-S and modified K-S methods remain under 50% in the first three seconds, with maximum values of 80% and 87% respectively within the first fifteen seconds for the same test set. The CEG method consistently scores higher throughout the fifteen-second selections.
机译:密钥查找是基于内容的音乐索引和检索中不可或缺的步骤。在本文中,我们提出了一种O(n)实时算法,用于从复音确定音频。我们使用带有局部最大值检测方案的标准快速傅立叶变换来从和弦音频中提取音高和音高强度。接下来,我们使用Chew的螺旋阵列效应中心发生器(CEG)算法从音高强度信息中确定关键点。我们使用莫扎特的《交响曲》测试了提出的系统。测试数据是从MIDI源产生的音频。该算法在前15秒内达到96%的最大正确键识别率,并在前3秒内超过90%。从提取的音高强度信息开始,我们将CEG算法的性能与经典的Krumhansl-Schmuckler(K-S)探针音调轮廓法和Temperley的K-S方法的改进版进行比较。对于K-S和改进的K-S方法,正确的键识别率在前三秒内保持在50%以下,对于同一测试集,在前十五秒内最大值分别为80%和87%。在15秒钟的选择中,CEG方法始终得分较高。

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