contents

[jelletreep]

Notes Animal sounds project

Background Research questions logistics Hard drives with TB of audio data by plane Lot of data Data on Yoda

Team and collaboration

Scientific problems: • Not a lot of vocalizations • Recordings Sanctuary, how representative is that

Annotations: • Raven for annotations • Speeding up annotation • Synthetic data

Machine learning: • SVM: feature extraction and selection • CNN: link to challenge, CNN selection, finetuning • <> • Interspeech challenge • Challenge test dataset is from sanctuary. How representative is this result in “rainforest” • Finetuning PANNS on training data

Results • Model performance • Publish dataset

Lessons learned: • Collaboration with ML audio expert • Involvement researcher • Data management • Code management (Matlab scripts, repo’s with playground folders, no real git workflow, documentation, package from early stage)

[jelletreep]

Todo Jelle:

• [ ] butter bandpass filter
• [ ] MFCC features (show spectrogram)
• [ ] recursive feature elimination
• [ ] features selection
• [ ] svm training
• [ ] results