Knowledge-based pattern recognition: a case study in acoustic-phonetic of speech

The various approaches proposed to solve the difficult problem of acoustic phonetic decoding (PD) are briefly recalled, including the hidden Markov model (HMM), which appears to be particularly efficient. It is then proposed to consider PD as a knowledge-intensive process, and the issues involved in the knowledge-based approach to this problem are identified. The APHODEX (acoustic expert) phonetic decoding system is used to illustrate this approach. Results obtained show that the knowledge acquired from expert phoneticians can substantially improve the performances of PD systems. The incorporation of this knowledge into efficient operational models such as HMMs or neural networks represents a good basis for further developments in the field.<>