Title :
Multiresolution time-frequency analysis of polyphonic music
Author :
Keren, R. ; Zeevi, Y.Y. ; Chazan, D.
Author_Institution :
Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel
Abstract :
Automatic transcription of polyphonic music is one of the difficult problems in the field of signal processing and analysis. One of the main reasons is that there exists no single scale of time-frequency representation, which is suitable for the detection of the wide range of features present in the musical sounds. The multiresolution Fourier transform (MFT) approach has been investigated, in order to overcome this problem by providing several time-frequency representations using a range of scales. This representation enables more flexibility in the analysis of polyphonic audio signals which requires a good feature separation. Transcription algorithms designed to work on MFT coefficients are shown to have a great potential and good transcription results are achieved for more complicated music performances, than currently possible by other techniques
Keywords :
Fourier transforms; acoustic signal detection; audio signal processing; music; signal representation; signal resolution; time-frequency analysis; MFT coefficients; automatic transcription; complicated music performances; feature detection; feature separation; multiresolution Fourier transform; multiresolution time-frequency analysis; musical sounds; polyphonic audio signals; polyphonic music; signal analysis; signal processing; time-frequency representation; transcription algorithms; Algorithm design and analysis; Data mining; Fourier transforms; Multiple signal classification; Sampling methods; Signal analysis; Signal processing; Signal processing algorithms; Signal resolution; Time frequency analysis;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1998. Proceedings of the IEEE-SP International Symposium on
Conference_Location :
Pittsburgh, PA
Print_ISBN :
0-7803-5073-1
DOI :
10.1109/TFSA.1998.721487