Extract Regions of Interest from Whale Song
Load a file that contains audio data from a Pacific blue whale, sampled at 4 kHz. The file is from the library of animal vocalizations maintained by the Cornell University Bioacoustics Research Program. The time scale in the data is compressed by a factor of 10 to raise the pitch and make the calls more audible. Convert the signal to a MATLAB® timetable.
whaleFile = fullfile(matlabroot,"examples","matlab","data","bluewhale.au"); [w,fs] = audioread(whaleFile); whale = timetable(seconds((0:length(w)-1)'/fs),w); % To hear, type soundsc(w,fs)
Open Signal Analyzer and drag the timetable to a display. Four features stand out from the noise. The first is known as a trill, and the other three are known as moans.
On the Display tab, click Spectrum to open a spectrum view and click Panner to activate the panner. Use the panner to create a zoom window with a width of about 2 seconds. Drag the zoom window so that it is centered on the trill. The spectrum shows a noticeable peak at around 900 Hz.
Extract the three moans to compare their spectra:
Center the panner zoom window on the first moan. The spectrum has eight clearly defined peaks, located very close to multiples of 170 Hz. Click the arrow next to Extract Signals and select
Between Time Limits.
Click Panner to hide the panner. Press the space bar to see the full signal. Click Zoom in X and zoom in on a 2-second interval of the time view centered on the second moan. The spectrum again has peaks at multiples of 170 Hz. Click the arrow next to Extract Signals and select
Between Time Limits.
Press the space bar to see the full signal. Click Data Cursors and select
Two. Place the time-domain cursors in a 2-second interval around the third moan. Again, there are peaks at multiples of 170 Hz. Click the arrow next to Extract Signals and select
Between Time Cursors.
Remove the original signal from the display by clearing the check box next to its name in the Signal table. Display the three regions of interest you just extracted. Their spectra lie approximately on top of each other. Move the frequency-domain cursors to the locations of the first and third spectral peaks. Asterisks in cursor labels indicate interpolated signal values.
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