Application of the Wigner distribution to speech analysis

The Wigner distribution, a time-frequency signal representation similar to the spectrogram, has recently been applied to speech analysis. It offers higher resolution than the spectrogram, but introduces artifacts that do not correspond to the components of the signal. These artifacts seem to be characterized by negative values of the Wigner distribution. If so, skilled experimental subjects should be able to visually identify and disregard the artifacts. Subjects examined spectrograms and Wigner distributions of a set of synthetic speech utterances, and performed a simple formant-tracking task (initial slope estimation) on them. The subjects performed this task marginally better using the Wigner distribution than the spectrogram. This performance advantage of the Wigner distribution held over the range of formant trajectories that the synthesizer could reliably produce. Performance depended critically on the subjects' understanding of artifacts. A theoretical prediction of a limit on formant slope, previously untested, was consistent with both spectrograms and Wigner distributions of natural speech. The overall conclusion is that the Wigner distribution is a viable alternative to the spectrogram for analysis of rapid spectrum changes. However, the burden of its greater complexity seems to outweigh its potential performance advantages.