Acoustic-phonetic approach to speech recognition based on event detection and linear discriminant analysis
Amit Juneja, Carol Espy-Wilson · The Journal of the Acoustical Society of America · 2001
An approach to speech recognition based on phonetic-feature theory was developed to recognize the E-set. The speech signal is first segmented into broad classes based on parameters for the manner phonetic features sonorant, syllabic, continuant, and strident, in addition to silence. The speech signal is divided into the regions: vowel, sonorant consonant, strong fricative, weak fricative, and stop. The events specified by the manner features are then used to extract parameters relevant for the place phonetic features. In particular, we extract parameters for the place phonetic features labial and alveolar for stops; and alveolar and palatal for strong fricatives. Decisions at this stage of recognition are based on an optimal linear combination of parameters. The linear weights are obtained from the training data by applying linear discriminant analysis. The TI46 database is used for training and testing. The results of our event-based system are compared to a standard MFCC and HMM based recognizer. [Work supported by NSF Grant SBR-9729688.]