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Acoustic detection of the short pulse call of Brydes whales using time domain features and hidden Marcov models
Thesis (MEng)--Stellenbosch University, 2020.
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| Format: | Thesis |
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Stellenbosch : Stellenbosch University
2020
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| _version_ | 1867613951988072448 |
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| access_status_str | Open Access |
| author | Wache Ngateu, Gaelle Venessa |
| author2 | Versfeld, Daniel Jaco J. |
| author_browse | Versfeld, Daniel Jaco J. Wache Ngateu, Gaelle Venessa |
| author_facet | Versfeld, Daniel Jaco J. Wache Ngateu, Gaelle Venessa |
| author_sort | Wache Ngateu, Gaelle Venessa |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MEng)--Stellenbosch University, 2020. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/108015 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:44:18.862Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/108015 Acoustic detection of the short pulse call of Brydes whales using time domain features and hidden Marcov models Wache Ngateu, Gaelle Venessa Versfeld, Daniel Jaco J. Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Time-domain reflectometry Acoustic localization Bryde's whales -- Detection Hidden Markov models UCTD Thesis (MEng)--Stellenbosch University, 2020. 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. AFRIKAANSE OPSOMMING: Die biologiese groep valkaansoorte word deesdae gereeld bestudeer as passiewe akoestiese monitering (PAM) word gereeld gebruik om die akoestiese seine wat deur walvisse, te midde van geraasgeluide wat deur een of ander man gemaak is tydens die vervoer, gas en olieverkenning of deur natuurlike klanke soos seismiese opnames, wind en reen. In hierdie navorsingswerk, die akoestiese sein van 'n kort polsslag van Bryde se walvisse word opgespoor met behulp van tyddomeinfunksies en verborge Markov-modelle (HMM). HMM word gebruik as 'n opsporing- en klassifikasietegniek vanwee die robuustheid en lae tydskompleksiteit tydens die opsporingsfase. Sommige parameters soos die keuse van funksies wat uittrek uit die akoestiese kortpulsoproep van Bryde's aan wal walvisse, die raamduur van elke oproep en die aantal toestande wat in die model gebruik word benvloed die optredes van die outomatiese HMM. Daarom, om uitvoerings te meet soos sensitiwiteit, akkuraatheid en vals positiewe tempo van die outomatiese HMM; drie keer domeineienskappe (gemiddelde drywing, gemiddelde en nul kruising) is onttrek uit a datastel van opnames van 44 uur 26 min naby Gordonsbaai in Valsbaai, Suid Afrika. Om hierdie kenmerke te onttrek, is die raamduur van elke vokalisasie ook onthul was drie keer gevarieerd; 1 ms, 5 ms en 10 ms. Die HMM het ook drie verskillende getalle gebruik van state (3 state, 5 state en 10 state) wat onafhanklik van mekaar verskil het evalueer die HMM. Op 'n algehele prestasie lewer die HMM die beste prestasies as dit 10 toestande gebruik met 'n kort raamduur van 1 ms en gemiddelde drywing as die onttrek funksie. Met betrekking hiertoe blyk die outomatiese HMM 99 : 56% te wees sensitief en betroubaar, aangesien dit 'n lae vals positiewe koers van 0: 1 met die gemiddelde toon krag afgelei as die beste tyddomeinfunksie wat gebruik word om die kort polsoproep van Kry die walvisse van Bryde met behulp van die HMM-tegniek.Die biologiese groep valkaansoorte word deesdae gereeld bestudeer as passiewe akoestiese monitering (PAM) word gereeld gebruik om die akoestiese seine wat deur walvisse, te midde van geraasgeluide wat deur een of ander man gemaak is tydens die vervoer, gas en olieverkenning of deur natuurlike klanke soos seismiese opnames, wind en reen. in hierdie navorsingswerk, die akoestiese sein van 'n kort polsslag van Bryde se walvisse word opgespoor met behulp van tyddomeinfunksies en verborge Markov-modelle (HMM). HMM word gebruik as 'n opsporing- en klassifikasietegniek vanwe die robuustheid en lae tydskompleksiteit tydens die opsporingsfase. Sommige parameters soos die keuse van funksies wat uittrek uit die akoestiese kortpulsoproep van Bryde's aan wal walvisse, die raamduur van elke oproep en die aantal toestande wat in die model gebruik word benvloed die optredes van die outomatiese HMM. Daarom, om uitvoerings te meet soos sensitiwiteit, akkuraatheid en vals positiewe tempo van die outomatiese HMM; drie keer domeineienskappe (gemiddelde drywing, gemiddelde en nul kruising) is onttrek uit 'n datastel van opnames van 44 uur 26 min naby Gordonsbaai in Valsbaai, Suid Afrika. Om hierdie kenmerke te onttrek, is die raamduur van elke vokalisasie ook onthul was drie keer gevarieerd; 1 ms, 5 ms en 10 ms. Die HMM het ook drie verskillende getalle gebruik van state (3 state, 5 state en 10 state) wat onafhanklik van mekaar verskil het evalueer die HMM. Op 'n algehele prestasie lewer die HMM die beste prestasies as dit 10 toestande gebruik met 'n kort raamduur van 1 ms en gemiddelde drywing as die onttrek funksie. Met betrekking hiertoe blyk die outomatiese HMM 99 : 56% te wees sensitief en betroubaar, aangesien dit 'n lae vals positiewe koers van 0: 1 met die gemiddelde toon krag afgelei as die beste tyddomeinfunksie wat gebruik word om die kort polsoproep van Kry die walvisse van Bryde met behulp van die HMM-tegniek. Masters 2020-02-24T08:58:25Z 2020-04-28T12:14:30Z 2020-02-24T08:58:25Z 2020-04-28T12:14:30Z 2020-03 Thesis http://hdl.handle.net/10019.1/108015 en Stellenbosch University xiv, 62 leaves : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Time-domain reflectometry Acoustic localization Bryde's whales -- Detection Hidden Markov models UCTD Wache Ngateu, Gaelle Venessa Acoustic detection of the short pulse call of Brydes whales using time domain features and hidden Marcov models |
| title | Acoustic detection of the short pulse call of Brydes whales using time domain features and hidden Marcov models |
| title_full | Acoustic detection of the short pulse call of Brydes whales using time domain features and hidden Marcov models |
| title_fullStr | Acoustic detection of the short pulse call of Brydes whales using time domain features and hidden Marcov models |
| title_full_unstemmed | Acoustic detection of the short pulse call of Brydes whales using time domain features and hidden Marcov models |
| title_short | Acoustic detection of the short pulse call of Brydes whales using time domain features and hidden Marcov models |
| title_sort | acoustic detection of the short pulse call of brydes whales using time domain features and hidden marcov models |
| topic | Time-domain reflectometry Acoustic localization Bryde's whales -- Detection Hidden Markov models UCTD |
| url | http://hdl.handle.net/10019.1/108015 |
| work_keys_str_mv | AT wachengateugaellevenessa acousticdetectionoftheshortpulsecallofbrydeswhalesusingtimedomainfeaturesandhiddenmarcovmodels |