Sinusoidal modeling parameter estimation via a dynamic channel vocoder model
Aaron Master · IEEE International Conference on Acoustics Speech and Signal Processing · 2002
We present a new analysis methodology for extracting accurate sinusoidal parameters from audio signals. The method combines modified vocoder parameter estimation with currently used peak detection algorithms in sinusoidal modeling. The current system processes input frame by frame, searching for peaks like a sinusoidal analysis model, but also dynamically selects vocoder channels, through which smeared peaks in the FFT domain are processed. This way, frequency trajectories of sinusoids of changing frequency within a frame may be accurately parametrized. We note that the computational expense incurred by using the new model is offset by the reduced frame rate allowed, and describe possible applications for the new model. We demonstrate that the current model is able to follow the changing frequencies in a long analysis frame, with accuracy greater than that found in a conventional sinusoidal model.