Automatic systems for estimating operator fatigue have application in safety-critical environments. A system which could estimate level of fatigue from speech would have application in domains where operators engage in regular verbal communication as part of their duties. Previous studies on the prediction of fatigue from speech have been limited because of their reliance on subjective ratings and because they lack comparison to other methods for assessing fatigue. In this paper, we present an analysis of voice recordings and psychophysiological test scores collected from seven aerospace personnel during a training task in which they remained awake for 60 h. We show that voice features and test scores are affected by both the total time spent awake and the time position within each subject’s circadian cycle. However, we show that time spent awake and time-of-day information are poor predictors of the test results, while voice features can give good predictions of the psychophysiological test scores and sleep latency. Mean absolute errors of prediction are possible within about 17.5% for sleep latency and 5–12% for test scores. We discuss the implications for the use of voice as a means to monitor the effects of fatigue on cognitive performance in practical applications.
Academic mobility is becoming increasingly popular for students and provides great opportunities to communicate with other people, get useful knowledge and experience and practice using a foreign language. Education abroad includes listening to lectures as one of the most common way of presenting information. Thus, students need preparation to understand foreign lecturers and be successful in their studies. Having studied 30 online lectures from diverse MOOCs, the authors identified that their structure is similar to traditional lectures. Consequently, the research was done with the use of academic lectures from the MOOC «Thermodynamics» to teach the experimental group of students from Peter the Great St. Petersburg Polytechnic University. For conducting the research the authors used a pedagogical experiment and descriptive statistical methods to analyse data received (T-statistics, chi-square and Fisher’s test). As a result, students from the experimental group showed better findings of listening comprehension skills with the average score of 65,5% compared to 44,4% of the control group. Moreover, the experimental group showed improvement in listening comprehension skills from the average score of 43% at the initial stage to 65,5% at the end of the experiment proving the effectiveness of learning activities the authors designed and used.
Abstract. Automatic systems for estimating operator fatigue have application in safety-critical environments. We develop and evaluate a system to detect fatigue from speech recordings collected from speakers kept awake over a 60-hour period. A binary classification system (fatigued/not-fatigued) based on time spent awake showed good discrimination, with 80% unweighted accuracy using raw features, and 90% with speaker-normalised features. We describe the data collection, feature analysis, machine learning and cross-validation used in the study. Results are promising for real-world applications in domains such as aerospace, transportation and mining where operators are in regular verbal communication as part of their normal working activities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.