On the use of symmetrized dot patterns for the visual characterization of speech waveforms and other sampled data

While the spectrogram (and related graphic analyses) have been invaluable in showing the general frequency content of an input signal, sometimes it is difficult for trained and untrained users to see on the spectrogram differences which are perceptible to the ear. In this paper, several demonstrations of a novel representation are presented which, in some cases, can make subtle differences in input signals obvious to the human analyst. The representation, a "symmetrized dot pattern" (SDP), provides a stimulus in which local visual correlations are integrated to form a global percept and can potentially be applied to the detection and characterization of significant features of any sampled data.