We are delighted to announce that Phincho Sherpa, a junior student from Long Island City School (New York City borough of Queens) has joined BirdVox for a one-month research internship under the mentorship of Dr. Vincent Lostanlen, as part of the ARISE program at the NYU Tandon School of Engineering. Below is her research proposal.
ARISE (Applied Research Innovations in Science and Engineering) is an intensive program for academically strong, current 10th and 11th grade New York City students with a demonstrated interest in science, technology, engineering and math. More information on ARISE can be found at this address.
Understanding the sounds of wildlife is paramount to the conservation of ecosystems. To this end, researchers in bioacoustics deploy recording devices on the field, thus resulting in massive amounts of digital audio data. The goal of this internship is to develop a new method for making sense of long audio files, lasting an entire day or more, without need to actually listen to them in full. In the case of short recordings, a convenient way to visualize sounds is the spectrogram, which represents the vocalizations of animals as bursts of acoustic energy in the time-frequency domain. For bird sounds, this method cannot be directly scaled up to long recordings, because the duration of a bird call (about one tenth of a second) is too short in comparison with the size of a long-term spectrogram pixel (about one minute). Phincho Sherpa will address this problem by modifying the representation of visual intensity in the time-frequency domain. In addition to energy, as is done in the conventional spectrogram, Phincho will explore other indices of acoustic complexity, such as entropy, flux, phase deviation, and per-channel energy normalization magnitude; and assign them to a multidimensional color map.
On August 16th, 2019, was held the yearly colloquium of the NYU ARISE program. Phincho Sherpa’s poster can be found below:
BirdVoxPaint: False-color spectrograms for long-duration bioacoustic monitoring
During her internship, Phincho Sherpa created an open-source Python module, named BirdVoxPaint, for computing spectrotemporal indices of acoustic complexity in long-duration recordings. The initial release (v0.1.0) offers five of these indices:
- acoustic complexity index (ACI) of Farina and Pieretti
- average energy
- entropy-based concentration of Sueur et al.
- maximum energy
- maximum spectral flux
BirdVoxPaint can be downloaded at the following link:
https://github.com/BirdVox/birdvoxpaint/releases/tag/v0.1.0
