Speech intelligibility measure for vocal control of an automaton
Michel Naranjo, Georgios Tsirigotis · AIP conference proceedings · 1998
The acceleration of investigations in Speech Recognition allows to augur, in the next future, a wide establishment of Vocal Control Systems in the production units. The communication between a human and a machine necessitates technical devices that emit, or are submitted to important noise perturbations. The vocal interface introduces a new control problem of a deterministic automaton using uncertain information. The purpose is to place exactly the automaton in a final state, ordered by voice, from an unknown initial state. The whole Speech Processing procedure, presented in this paper, has for input the temporal speech signal of a word and for output a recognised word labelled with an intelligibility index given by the recognition quality. In the first part, we present the essential psychoacoustic concepts for the automatic calculation of the loudness of a speech signal. The architecture of a Time Delay Neural Network is presented in second part where we also give the results of the recognition. The theory of the fuzzy subset, in third part, allows to extract at the same time a recognised word and its intelligibility index. In the fourth part, an Anticipatory System models the control of a Sequential Machine. A prediction phase and an updating one appear which involve data coming from the information system. A Bayesian decision strategy is used and the criterion is a weighted sum of criteria defined from information, minimum path functions and speech intelligibility measure.