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L R Rabiner

Publications and source records attributed to L R Rabiner.

13 recordsLinked to original sources
PubMed1984

On duration and smoothing rules in a demisyllable-based isolated-word recognition system.

In a recently proposed approach to isolated-word recognition, word reference templates are constructed from a universal set of demisyllable units by concatenating the appropriate demisyllables for each vocabulary item. A dynamic time warping (DTW) algorithm is used to align test and reference patterns optimally. Nevertheless some sort of syllable duration preadjustment is necessary because of the large potential difference in duration between isolated and in-context syllables. We have found that a simple rule that reduces the length of rhyme (final) demisyllables in nonword-final stressed syllables to approximately half their isolated-syllable duration provides recognition accuracy as high as that attained through use of complex, highly context-sensitive rules. In addition to its practical application, this result can be regarded as a further demonstration of the power of DTW. We have also investigated the requirements for parameter smoothing at demisyllable boundaries. We find that an optimal window duration for smoothing is about 60-90 ms, but that failure to smooth reduces recognition accuracy only about 2% in an 1109 word test set; that linear and parabolic smoothing are equally effective; and that it does not appear that recognition accuracy can be improved by smoothing in certain phonetic contexts only. Taken together, these results can be viewed as confirming the suitability of the demisyllable as the basic unit in recognition systems.

Humans↗
PubMed1979

Considerations in applying clustering techniques to speaker-independent word recognition.

Recent work at Bell Laboratories has demonstrated the utility of applying sophisticated pattern recognition techniques to obtain a set of speaker-independent word templates for an isolated word recognition system [Levinson et al.,IEEE Trans. Acoust. Speech Signal Process. ASSP-27 (2), 134--141 (1979); Rabiner et al., IEEE Trans. Acoust. Speech Signal Process.(in press)]. In these studies, it was shown that a careful experimenter could guide the clustering algorithms to choose a small set of templates that were representative of a large number of replications for each word in the vocabulary. Subsequent word recognition tests verified that the templates chosen were indeed representative of a fairly large population of talkers. Given the success of this approach, the next important step is to investigate fully automatic techniques for clustering multiple versions of a single word into a set of speaker-independent word templates. Two such techniques are described in this paper. The first method uses distance data (between replications of a word) to segment the population into stable clusters. The word template is obtained as either the cluster minimax, or as an averaged version of all the elements in the cluster. The second method is a variation of the one described by Rabiner [IEEE Trans. Acoust. Speech Signal Process. ASSP-26 (3), 34--42 (1978)] in which averaging techniques are directly combined with the nearest neighbor rule to simultaneously define both the word template (i.e., the cluster center) and the elements in the cluster. Experimental data show the first method to be superior to the second method when three or more clusters per word are used in the recognition task.

Humans↗