A Method for Evaluating the Accuracy of Vocal Art Performance of Singers’ Voices Based on Sensor Space Localization Algorithm

Recently, research on singing assessment has focused on analyzing singer characteristics rather than building an automated evaluating approach. Hence, there are many methods for evaluating the accuracy of singer’s singing performance. Traditional methods mostly use quantitative analysis approach for the accuracy analysis of vocal artistic performance, and the results have obvious ambiguity and correlation. Therefore, this paper proposes a method for evaluating the accuracy of vocal art expression of singers’ voices based on a sensor spatial localization algorithm. The adaptive cascade retrieval control approach is used to find and mine the singers’ performance based on their voice characteristics. The sensor spatial location algorithm and huge vocal music resources with high precision are utilized to locate the vocal music sources in the mining results. The vocal music of the singers is received through the vocal music preprocessing platform, which sends and controls musical compositions. The adaptive frequency’s shift filter and the wavelet transform method are used to filter out any noise in the music. Finally, the accurate evaluation of singer vocal artistic performance is realized from the aspects of music beat detection, note boundary accuracy analysis, and voiced segment accuracy detection. The experimental results show that our proposed method can reduce the error of the sound source’s localization and can effectively filter out the noise in the music signal.