A Dynamic, Feature-Based Approach Modeling and Recognition to Speech
An overview of a statistical paradigm for speech recog- nition is given where phonetic and phonological knowledge sources are seaimlessly integrated into the structure of a speech model. A unifying computational formalism is outlined in which the sub-models for the dis- crete, feature-based phonological and the continuous, dynamic phonetic processes in human speech production are computationally interfaced, enabling global optimization of the model parameter sets that economi- cally characterize distinct sources of speech variabilities. The formalism is founded on a rigorous mathematical basis, and is developed to aim at overcoming key limitations of current speech recognition technology.