Third European Conference on Speech Communication and Technology

Berlin, Germany
September 22-25, 1993


Speech Recognition Using the Atomic Speech Units Constructed from Overlapping Articulatory Features

Li Deng (1,2), Don Sun (1,3)

(1) Spoken Language Systems Group, Laboratory for Computer Science, Massachusetts Institute of Technology, Cambridge, USA
(2) Department of Electrical and Computer Engineering - University of Waterloo, Waterloo, Ontario, Canada
(3) Department of Statistics - University of Waterloo, Waterloo, Ontario, Canada

We report our recent development of a feature-based general statistical framework for automatic speech recognition. The design of the feature-based atomic units of speech is aimed at a parsimonious scheme to share the inter-word and inter-phone speech data and at a unified way to account for the context-dependent behaviors in speech. We provide detailed descriptions of the design considerations for the recognizer and of key aspects of the design process. This process, which we call lexicon "compilation", consists of three elements: 1) establishing a feature-specification system; 2) constructing a probabilistic and fractional temporal overlapping pattern across the features; and 3) mapping from the feature-overlap pattern to a state-transition graph. A standard phonetic classification task from the TIMIT database is used as a testbed to evaluate the performance of the recognizer. The experimental results show error-rate reductions ranging from 15% to 27% compared with a conventional context-independent phonetic classifier.

Keywords: speech recognition, features, non-linear phonology, hidden Markov model, articulatory gestures

Full Paper

Bibliographic reference.  Deng, Li / Sun, Don (1993): "Speech recognition using the atomic speech units constructed from overlapping articulatory features", In EUROSPEECH'93, 1635-1638.