Title :
Automatic Transcription of Polyphonic Music Based on the Constant-Q Bispectral Analysis
Author :
Argenti, Fabrizio ; Nesi, Paolo ; Pantaleo, Gianni
Author_Institution :
Dept. of Electron. & Telecommun. Eng. (DET), Univ. of Florence, Florence, Italy
Abstract :
In the area of music information retrieval (MIR), automatic music transcription is considered one of the most challenging tasks, for which many different techniques have been proposed. This paper presents a new method for polyphonic music transcription: a system that aims at estimating pitch, onset times, durations, and intensity of concurrent sounds in audio recordings, played by one or more instruments. Pitch estimation is carried out by means of a front-end that jointly uses a constant-Q and a bispectral analysis of the input audio signal; subsequently, the processed signal is correlated with a fixed 2-D harmonic pattern. Onsets and durations detection procedures are based on the combination of the constant-Q bispectral analysis with information from the signal spectrogram. The detection process is agnostic and it does not need to take into account musicological and instrumental models or other a priori knowledge. The system has been validated against the standard Real-World Computing (RWC)-Classical Audio Database. The proposed method has demonstrated good performances in the multiple F0 tracking task, especially for piano-only automatic transcription at MIREX 2009.
Keywords :
audio signal processing; estimation theory; information retrieval; music; 2D harmonic pattern; MIR; RWC-classical audio database; audio recordings; automatic music transcription; constant-Q bispectral analysis; duration detection; music information retrieval; onset detection; pitch estimation; polyphonic music transcription; real-world computing classical audio database; signal spectrogram; Estimation; Filter bank; Fourier transforms; Harmonic analysis; Hidden Markov models; Psychoacoustic models; Spectral analysis; Audio signals processing; bispectrum; constant-Q analysis; higher order spectra; music information retrieval (MIR); polyphonic music transcription;
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
DOI :
10.1109/TASL.2010.2093894