The New Algorithm for Speech Control in the Cockpit

Abstract

Speech technologies are being developed intensively in the recent years, especially the automatic speech recognition as an additional input method in human interface and technical devices. Most of the known algorithms for speech control have small probability of correct recognition. Widespread methods, like Markov models and neural networks, which require large processing power, allow recognizing the words with a probability of no more than 85–92 %. Such accuracy is not enough to use the voice control on board of a modern aircraft. The article is devoted to a problem of improving the automatic speech recognition’s accuracy. A version of word recognition algorithm based on the classical approach is suggested, it includes the comparison with the patterns. In this work to improve the recognition’s accuracy a new method of calculating a similarity measurement between the recognizable word and the pattern, which based on z-Fisher transformation, is described. This article also contains an algorithm’s modification that takes into account the fixed ratios with the patterns of other words and uses the words adjustment to the pattern with dynamic programming elements. The usage of fixed relations between words provides additional information, which positively affects the recognition. The experimental results of the developed algorithm’s approbation on a large amount of speech data are presented.