Exploiting complementary aspects of phonological features in automatic speech recognition

This paper presents techniques for exploiting complementary information contained in multiple definitions of phonological feature systems. Three different feature systems, differing in their structure and in the acoustic phonetic features they represent, are considered. A two stage process involving a mechanism for frame level phonological feature detection and a mechanism for decoding phoneme sequences from features is implemented for each phonological feature system. Two methods are investigated for integrating these features with MFCC based ASR systems. First, phonological feature and MFCC based systems are combined in a lattice re-scoring paradigm. Second, confusion network based system combination (CNC) is used to combine phone networks derived from phonological distinctive feature (PDF) and MFCC based systems. It is shown, using both methods, that phone error rates can be reduced by as much as 15% relative to the phone error rates obtained for any individual feature stream.