Before revision:  3. We provide a case study showing how GIBBONR functions can be used in a workflow to classify and detect Bornean gibbon (Hylobates muelleri) calls in long-term recordings from Danum Valley Conservation Area, Sabah Malaysia. 4. Machine learning is currently one of the most rapidly growing fields-- with applications across many disciplines-- and our goal is to make commonly used signal processing techniques and machine learning algorithms readily available for ecologists who are interested in incorporating bioacoustics techniques into their research.
After revision:  3. We provide a case study showing how GIBBONR functions can be used in a workflow to classify and detect Bornean gibbon (Hylobates muelleri) calls in long-term recordings from Danum Valley Conservation Area, Sabah , Malaysia. Machine learning is currently one of the most rapidly growing fields-- with applications across many disciplines-- and our goal is to make commonly used signal processing techniques and machine learning algorithms readily available for ecologists who are interested in incorporating bioacoustics techniques into their research.