Effect of Noise on Automatic Speech Recognition System Error Rate

Abstract

Many studies have indicted that stress and workload can effect the recognition accuracy of the speech recognition system. This can include noise, vibration, G-force, information overload, vocal quality in noise, vocal quality and psychological stress, concurrent task performance and vocal fatigue. The commercially available speech recognition system has not yet reached the perfect design to recognize natural human speech. The military application of automatic speech recognition systems has been studied in a wide arrangement. Verbex’ Voice Master was recommended in its instruction book as especially suited well for use in a noisy environment. This system was selected as a candidate system for use in cockpits. Before implementing it in the cockpit, its strengths and weaknesses for special utterances need to be tested in a laboratory environment. The purpose of the study was to investigate the effects of noise on recognition accuracy in dual-task performance. The experiment was carried out in a noise-insulated room. The Verbex’ Voice Master speech recognition system was installed into the computer. Eleven male Swedish students were the subjects. Two noise levels were set up with a combination of mental workload and physical workload. The results showed that without noise and mental workload, the recognition accuracy could be as good as 99.4%. With noise and mental workload, the recognition accuracy could be reduced to 95%. The results indicated that noise had significant effects on the computer error while mental workload had significant effects on both subject error and computer error.