Representation of bioacoustic sound data through graphical similarities to enhance knowledge discovery

Autonomous detection and classification of species through bioacoustics sound has been an ongoing and challenging problem due to noise, overlapping sound, and varying frequency components. This work assesses bioacoustic sound data through speech patterns similarities by utilizing graphical representations of features found in spectrograms. Speech within the received sound can be characterized as individual components within the spectrogram that can be used to identify species. In this work, individual components are connected high PSD dB values in the spectrogram that form unique shapes. By representing these components through graphical representations, similarities of speech can be seen as repeating patterns across larger collected data sets that can be associated with certain behaviors of species. An example resulting graphical representation is presented through a sample humpback whale speech collected. [This research is funded by the Office of Naval Research under Grant No. N00014-19-1-2609.]