Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025
A new technique for constructing Markov models for the acoustic representation of words is described. Word models are constructed from models of sub-word units called fenones. Fenones represent very short speech events, and are obtained automatically through the use of a vector quantizer. The fenonic baseform for a word—i.e., the sequence of fenones used to represent the word—is derived automatically from one or more utterances of that word. Since the word models are all composed from a small inventory of sub-word models, training for large-vocabulary speech recognition systems can be accomplished with a small training script. A method for combining phonetic and fenonic models is presented. Results of experiments with speaker-dependent and speaker-independent models on several isolated-word recognition tasks are reported. Comparative results with phonetics-based Markov models and template-based DP matching are also given. © 1993 IEEE
Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025
Arnon Amir, M. Lindenbaum
Computer Vision and Image Understanding
Bowen Alpern, Larry Carter
VIS 1991
Jonathan H. Connell, Nalini K. Ratha, et al.
ICIP 2002