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Georgia Atkinson

Acoustic identification of cetaceans.

Supervisors

Project description

Dolphins, whales and porpoises are cetaceans. Modelling cetacean population dynamics is paramount for effective conservation and management. Cetaceans are prime candidates for modelling ecosystem change as they are at the top of the food chain within the ocean. Moreover, they can be used to assess the risk presented by anthropogenic activities.

Methodologies for cetacean research include passive acoustic monitoring (PAM). This allows for monitoring of cetacean occurrence and behaviour ecology through underwater recording. PAM systems collect and store high volumes of data. Thus, there is a need for automated solutions to detect and classify cetacean vocalisations. Current technologies can identify cetacean species using vocalisations. But they do not harness deep learning techniques or use signature whistles to identify individuals within a species.

We are designing a system to detect and classify white-beaked dolphin whistles. We are using signal processing and deep learning techniques. White-beaked dolphins migrate through the North-East of England between June and October each year. There is evidence to suggest the whistles that they produce are distinct. This means that they can be identified by these whistles, known as signature whistles. There is also evidence from a recent study to suggest their health is in decline. Thus, monitoring of these groups is of the utmost importance.

Publications

Interests

Bioacoustics, deep learning, marine conservation.

Qualifications

  • MMathStat – Newcastle University (2017)
  • PGDip Cloud Computing for Big Data – Newcastle University (2018)

 

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