Extracting More Detail from the Spectrum with Phase Distortion Analysis

Paul Masri; Nishan Canagarajah
DAFx-1998 - Barcelona
In the sinusoidal analysis of sound, using the Short Time Fourier Transform (STFT), there is the assumption that the signal is locally stationary within each FFT frame. If, as in practice, this assumption is violated, the spectrum becomes distorted. Phase Distortion Analysis (PDA) was introduced in 1995 [1] to enhance the analysis of degraded peaks, by using the distortion itself as a source of information about the signal nonstationarity. It was shown that the first order frequency and amplitude modulation could be measured from the degree of phase shift close to the maximum of the mainlobe peak. This paper presents advances with the PDA technique, in particular a neural network implementation that makes estimation robust to noise. The capability to analyse nonstationarities relaxes the restraint on keeping the FFT analysis window short and therefore effectively improves time-frequency resolution. This, in turn, promises greater analysis-synthesis quality through improved identification and tracking of partials during the analysis phase.