Identifying rale sounds in chickens using audio signals for early disease detection in poultry

Extreme learning machine (ELM) and support vector machine (SVM) classifiers are developed to detect rales (a gurgling sound that is a symptom of respiratory diseases in poultry). These classifiers operate on Mel-scaled spectral features calculated from recordings of healthy and sick chickens during a vaccine trial. Twenty minutes of labeled data were used to train and test the classifiers, then they were run on the full 25 days of continuous recordings from the healthy and sick chickens. The resulting detection rate follows the course of the disease and clearly distinguishes between the healthy and sick chickens. These results improve on our previous findings from the same data, and demonstrate the potential for automated acoustic monitoring of the health of commercial flocks.