Accession Number : ADA259780


Title :   Segment-Based Acoustic Models for Continuous Speech Recognition


Descriptive Note : Progress rept. Jul-Dec 1992


Corporate Author : BOSTON UNIV MA


Personal Author(s) : Ostendorf, Mari ; Rohlicek, J R


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a259780.pdf


Report Date : 22 Dec 1992


Pagination or Media Count : 21


Abstract : This paper presents an overview of the Boston University continuous word recognition system, which is based on the Stochastic Segment Model (SSM). The key components of the system described here include: a segment-based acoustic model that uses a family of Gaussian distributions to characterize variable length segments; a divisive clustering technique for estimating robust context-dependent models; and recognition using the N-best rescoring formalism, which also provides a mechanism for combining different knowledge sources (e.g. SSM and HMM scores). Results are reported for the speaker-independent portion of the Resource Management Corpus, for both the SSM system and a combined BU-SSM/BBN-HMM system.


Descriptors :   *SPEECH RECOGNITION , *ACOUSTICS , *WORD RECOGNITION , *GAUSSIAN QUADRATURE , MANAGEMENT , MODELS , RESOURCE MANAGEMENT , DISTRIBUTION , VARIABLES , CLUSTERING


Subject Categories : Linguistics
      Cybernetics
      Voice Communications


Distribution Statement : APPROVED FOR PUBLIC RELEASE