Accession Number : ADA460569


Title :   Tied Mixtures in the Lincoln Robust CSR


Corporate Author : MASSACHUSETTS INST OF TECH LEXINGTON LINCOLN LAB


Personal Author(s) : Paul, Douglas B


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a460569.pdf


Report Date : Jan 1989


Pagination or Media Count : 11


Abstract : HMM recognizers using either a single Gaussian or a Gaussian mixture per state have been shown to work fairly well for 1000-word vocabulary continuous speech recognition. However, the large number of Gaussians required to cover the entire English language makes these systems unwieldy for large vocabulary tasks. Tied mixtures offer a more compact way of representing the observation pdf's. We have converted our independent mixture systems to tied mixtures and have obtained mixed results: a 13% improvement in speaker-dependent recognition without cross-word triphone models, but no improvement in our speaker-dependent system with cross-word boundary triphone models or in our speaker-independent system. There is also a reduction in CPU requirements during recognition--but this is counter-balanced by an increase during training. This paper also includes a comment on the validity of the DARPA program's evaluation test system comparisons.


Descriptors :   *SPEECH RECOGNITION , MIXTURES , VOCABULARY , STATISTICAL PROCESSES , MARKOV PROCESSES , ENGLISH LANGUAGE


Subject Categories : Voice Communications


Distribution Statement : APPROVED FOR PUBLIC RELEASE