A connected digit recognizer is proposed in which a set of isolated word templates is used as reference patterns and an unconstrained dynamic time warping algorithm is used to literally spot the digits in the string. Segmentation boundaries between digits are obtained as the termination point of the dynamic path from the previous time warp. A region around the boundary is searched for the optimum starting point for the succeeding digit. At each stage the recognizer keeps track of a set of candidate digit strings for each test string. The string with the smallest accumulated distance is used as the preliminary string estimate. For variable length digit strings of from 2 to 5 digits (where the recognizer was not told the length of the string), word error rates of about 2-3% and string error rates on the order of 8% were obtained for both speaker dependent and speaker independent systems.

In a simulation of soft decision demodulation-interpolation for digital speech transmission, it has been noted that signal-to-noise ratio gains due to the technique are greater with nonadaptive and periodically adaptive quantizers than with instantaneously adaptive quantizers; further, the gains are greater with PCM than with differential PCM. Our results for nonadaptive PCM reinforce those in a recent analytical paper by Sundberg [1].

An automatic word recognizer is used to accept strings of spelled letters spoken in isolation. The output of the recognizer is a set of best candidate letters for each letter spoken in the string. Candidate strings forming spelled last names and initials are compared to name strings obtained from a telephone directory stored in a disk file. A systematic search is carried out to find a matching entry in the directory. An evaluation has been carried out with ten talkers spelling lists of names extracted from an 18,000 entry telephone directory. Although the median acoustic error rate per spelled letter is approximately 20%, the median error rate in furnishing the requested directory entry is approximately 4%.