Abstract: Speech signals are analyzed by correlating a sequence of samples to derive a sliding average magnitude difference function (SAMDF) whereby histograms are formed which are compressed and normalized to form histogram sequences representing the speech signal for comparison and recognition.

Abstract: A method and apparatus for generating a signal transformation useful in signal processing. According to the preferred embodiment, a signal, e.g., a speech waveform, is first converted into a sequence of digital data samples, and a reference position along a first sub-part of the sequence is then selected. A "weighted" histogram corresponding to the reference position is then generated according to a correlation function. Thereafter, a new reference position is selected, for example, at a sub-part of the sequence located a pitch period of the signal from the original reference position, and an additional histogram is generated for this sub-part. The plurality of histograms comprise the transformation of the signal, which retains a substantial part of the informational content of the original signal. Therefore, the transformation is then used as the signal itself in signal processing applications such as speech compression and synthesis.