Extract Regions of Interest from Whale Song

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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,'例子','matlab','数据','bluewhale.au'); [w,fs] = audioread(whaleFile); whale = timetable(seconds((0:length(w)-1)'/fs),w);% To hear, type soundsc(w,fs)

OpenSignal Analyzerand drag the timetable to a display. Four features stand out from the noise. The first is known as atrill, and the other three are known asmoans。

On theDisplaytab, clickSpectrumto open a spectrum view and click泛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:

将Panner Zoom窗口中心在第一个呻吟处。频谱具有八个明确定义的峰，位于170 Hz的倍数非常接近。点击提取信号▼和选择Between Time Limits。
点击泛to hide the panner. Press the space bar to see the full signal. ClickZoom in Xand 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提取信号▼和选择Between Time Limits。
Press the space bar to see the full signal. ClickData Cursors▼和选择Two。将时域光标放在第三呻吟周围的2秒间隔。同样，倍数为170Hz的峰值。点击提取信号▼和选择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.

Extract Regions of Interest from Whale Song

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