Showing papers on "Segmentation-based object categorization published in 1970"

Acoustic segmentation of speech

Abstract: A brief argument is presented for the need for automatic speech segmentation both to facilitate automatic speech recognition and for its theoretical linguistic importance. The problem of speech segmentation in the acoustic domain using a digital computer is examined in detail, that is, of determining an acoustic partition in time which has linguistic relevance. This problem is viewed, in more general terms, as that of detecting transitions, in a globally non-stationary process, from one local stationary state to another. Non-stationary analyses are approximated by considering short fixed length time series sections as seen through a window which moves by a fixed increment. Various non-stationary signal representations are explored in order to establish a feature space suitable for applications to segmentation. Spectral representations are generated only as a reference space for comparison of an automatic segmentation procedure with the linguistically determined segmentation of any given speech sample. Temporal representations of the zero crossings of speech signals are explored in detail. In particular the central sample moments of the reciprocal zero crossings as a function of time are used as input to a simple segmentation algorithm. The results of a demonstration of this algorithm show that speech segmentation as defined is possible by non-human means.