Knowledge based fundamental and harmonic frequency detection in polyphonic music analysis

Li, Xiaoquan and Yan, Yijun and Ren, Jinchang and Zhao, Huimin and Zhao, Sophia and Soraghan, John and Durrani, Tariq; Liang, Qilian and Mu, Jiasong and Jia, Min and Wang, Wei and Feng, Xuhong and Zhang, Baoju, eds. (2018) Knowledge based fundamental and harmonic frequency detection in polyphonic music analysis. In: Communications, Signal Processing, and Systems. Springer, CHN, pp. 591-599. ISBN 9789811065705 (

[thumbnail of Li-etal-ICCSPS-2017-Knowledge-based-fundamental-and-harmonic-frequency-detection]
Text. Filename: Li_etal_ICCSPS_2017_Knowledge_based_fundamental_and_harmonic_frequency_detection.pdf
Accepted Author Manuscript

Download (545kB)| Preview


In this paper, we present an efficient approach to detect and tracking the fundamental frequency (Fo) from 'wav' audio. In general, music Fo and harmonic frequency show the multiple relations; therefore frequency domain analysis can be used to track the Fo. The model includes the harmonic frequency probability analysis method and useful pre-post processing for multiple instruments. Thus, the proposed system can efficiently transcribe polyphonic music, while taking into account the probability of Fo and harmonic frequency. The experimental results demonstrate that the proposed system can successful transcribe polyphonic music, achieved the quite advanced level.


Li, Xiaoquan, Yan, Yijun ORCID logoORCID:, Ren, Jinchang ORCID logoORCID:, Zhao, Huimin, Zhao, Sophia, Soraghan, John ORCID logoORCID: and Durrani, Tariq; Liang, Qilian, Mu, Jiasong, Jia, Min, Wang, Wei, Feng, Xuhong and Zhang, Baoju