Browsing by Author "Wache Ngateu, Gaelle Venessa"

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    Acoustic detection of the short pulse call of Brydes whales using time domain features and hidden Marcov models
    (Stellenbosch : Stellenbosch University, 2020-03) Wache Ngateu, Gaelle Venessa; Versfeld, Daniel Jaco J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.
    ENGLISH ABSTRACT: The biological group of cetaceans is frequently studied nowadays as passive acoustic monitoring (PAM) is commonly used to extract the acoustic signals produced by cetaceans, in the midst of noise sounds made by either man during shipping, gas and oil explorations or by natural sounds like seismic surveys, wind and rain. In this research work, the acoustic signal of short pulse call of inshore Bryde's whales is detected using time domain features and hidden Markov models (HMM). HMM is deployed as a detection and classi cation technique due to its robustness and low time complexity during the detection phase. However, some parameters such as the choice of features to be extracted from the acoustic short pulse call of inshore Bryde's whales, the frame durations of each call and the number of states used in the model affect the performances of the automated HMM. Therefore, to measure performances like sensitivity, accuracy and false positive rate of the automated HMM; three time domain features (average power, mean and zero-crossing rate) were extracted from a dataset of 44hr26mins recordings obtained close to Gordon's bay in False bay, South Africa. Moreover, to extract these features the frame durations of each vocalisation was varied thrice; 1 ms, 5 ms and 10 ms. Also, the HMM used three different number of states (3 states, 5 states and 10 states) which were varied independently so as to evaluate the HMM. On an overall performance, the HMM yields best performances when it uses 10 states with a short frame duration of 1 ms and average power as the extracted feature. With regard to this, the automated HMM shows to be 99:56% sensitive, and dependable as it exhibits a low false positive rate of 0:1 with average power inferred as the best time domain feature used to detect the short pulse call of inshore Bryde's whales using the HMM technique.