Realization and design of a pilot assist decision-making system based on speech recognition
This work addresses pilot decision-making in aviation control through a novel speech-based system, though it appears incremental in applying existing speech recognition techniques to this domain.
The paper tackled pilot assist decision-making by developing a speech recognition system using LPCC and DTW for isolated-word recognition, achieving satisfactory accuracy and control effects in a HIL aircraft simulation platform.
A system based on speech recognition is proposed for pilot assist decision-making. It is based on a HIL aircraft simulation platform and uses the microcontroller SPCE061A as the central processor to achieve better reliability and higher cost-effect performance. Technologies of LPCC (linear predictive cepstral coding) and DTW (Dynamic Time Warping) are applied for isolated-word speech recognition to gain a smaller amount of calculation and a better real-time performance. Besides, we adopt the PWM (Pulse Width Modulation) regulation technology to effectively regulate each control surface by speech, and thus to assist the pilot to make decisions. By trial and error, it is proved that we have a satisfactory accuracy rate of speech recognition and control effect. More importantly, our paper provides a creative idea for intelligent human-computer interaction and applications of speech recognition in the field of aviation control. Our system is also very easy to be extended and applied.