Lots of animals produce tonal calls. The acoustic characteristics of tonal sounds may help us to identify the species and behavior of calling animals. However, some animals like cetaceans, have a highly complex repertoire of tonal sounds. This elevates the difficulty of using automatic detection method in the passive acoustic monitoring.
In terms of this, I developed this program to help people use passive acoustic monitoring to study the animals’ tonal sounds. The purpose of this program is to decrease the labor work of detecting animals’ vocalizations by passive acoustic monitoring. The current program can detect multiple types of tonal sound without training or using sound template. The detection is based on the prominent of tonal appearance on the spectrogram.
The detection target of this program primary focus on “tonal sounds”, but it is also possible to detect “burst-pulses” and other “tonal noise” with strong tonal appearance. This program aims to work for everyone. It not only helps user to detect the occurrence of calls, but also provide information on their acoustic features so that user can use those information for further analysis.
The following figure is a demonstration of my algorithm.
The detection process include three main steps: 1. remove ambient noise, 2. extract tonal spectral peaks, and 3. noise filtering.
- Spectrograms of sound recordings are produced using fast Fourier transform (FFT) with the Hamming window. Ambient noise is removed by pre-whitening spectrograms. Spectrograms are further smoothed using a Gaussian kernel.
- Tonal sounds are detected by applying two thresholds (SNR and tonality). If the instantaneous frequency bandwidth of tonal sound is suitable, the peak frequency is extracted by finding the local maximum in the power spectrum.
- A noise filter is employed to exclude broadband noise and isolated narrowband noise. The tonal spectral peaks are claimed as adopted frequencies of animals’ tonal sound after noise filtering.
Detail of the local-max detector for tonal sound is available in the following publications:
Lin, Tzu-Hao, Chou, Lien-Siang, Akamatsu, Tomonari, Chan, Hsiang-Chih, Chen, Chi-Fang. (2013) An automatic detection algorithm for extracting the representative frequency of cetacean tonal sounds. Journal of the Acoustical Society America, 134: 2477-2485.
If you are interested, please feel free to contact me. This program is free of charge and we can cooperate together! Please also take a look at the operation manual of this program so that you can understand the system requirement and the possible application.
Tzu-Hao (Harry) Lin