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This paper describes a new algorithm of the auditory scene analysis, by which we can automatically choose a single sound stream from many background ones and reconstruct its original waveform. The features of our algorithm are as follows: 1) Efficient use of harmonics structure, i.e., stream is characterized by pitch and its dynamics; therefore it will be segregated by a time-varying comb filter. 2) Analysis and synthesis in the wavelet domain for extracting a stream so that its spectrum is invariant with the pitch estimation error. 3) The use of Parzen's density estimate and non-parametric Kalman filter for the optimum and multimodal tracking of pitch candidates. This algorithm is examined by several simulations and experiments using some artificial and real world data.

Multiple Pitch Tracking and Harmonic Segregation Algorithm for Auditory Scene Analysis