Audio Analysis: Making Sense of the Data
Introduction to Bioacoustics Analysis
Audio analysis is a critical component of bioacoustics research, enabling scientists to interpret and understand wildlife sounds effectively. By utilizing advanced technologies and software, researchers can gain insights into species behavior, communication patterns, and ecological interactions.
BirdNET
BirdNet is an innovative tool developed by the Cornell Lab of Ornithology and other collaborators that uses machine learning algorithms to identify bird species from audio recordings. It allows users to process recordings and obtain species identification, making it an invaluable resource for both researchers and citizen scientists. Key features of BirdNet include:
- Species Recognition: BirdNet can identify a wide range of bird species based on their vocalizations, providing a powerful tool for monitoring avian populations.
- User-Friendly Interface: The platform is designed to be accessible, allowing users to easily upload audio files and receive identification results.
- Continuous Improvement: As more users contribute data, BirdNet’s machine learning models improve, enhancing accuracy and expanding the range of identifiable species.
OpenSoundscape
Opensoundscape is another valuable but more advanced resource that facilitates large-scale audio analysis for ecological research. It provides an open-source platform for managing and analyzing wildlife sound data with machine learning models. Key features include:
- Load and manipulate audio files
- Create and manipulate spectrograms
- Train convolutional neural networks (CNNs) on spectrograms with PyTorch
- Run pre-trained CNNs to detect vocalizations
NoiseReduce
NoiseReduce is not a tool for automating detections, but it can dramatically reduce noise both from self noise as well as certain long duration ambient noise sources(traffic, wind, planes, etc). We think it's an excellent tool that can increase detectability and is worth incorporating into bioacoustics processing. See the detailed description from the author below:
"Noisereduce is a noise reduction algorithm in python that reduces noise in time-domain signals like speech, bioacoustics, and physiological signals. It relies on a method called "spectral gating" which is a form of Noise Gate. It works by computing a spectrogram of a signal (and optionally a noise signal) and estimating a noise threshold (or gate) for each frequency band of that signal/noise. That threshold is used to compute a mask, which gates noise below the frequency-varying threshold."
Raven Pro
While not entirely free, Raven Pro offers a free trial and is widely used for sound analysis in ecological research. It allows users to visualize, annotate, and analyze audio recordings, making it suitable for detailed bioacoustics studies.
Audacity
This open-source audio editing software provides essential features for analyzing and editing audio recordings. Users can visualize audio files with spectrograms, apply filters, and perform basic frequency analysis, making it a versatile tool for certain audio assessments.