I am working on a sound to detect when the sound beep starts using librosa in Python. When I plot the detected time, it has some offset as shown with a red line in the figure. This offset changes if the interval between the beeps changes. Since I want a robust method that detects the start of the wavelet in sound for variable beeps interval, How can I remove this offset?
Figure with Onset detection and the Difference between the intervals
x, sr = librosa.load('c.wav')
plt.figure(figsize=(30, 7))
librosa.display.waveplot(x, sr=sr)
onset_frames=librosa.onset.onset_detect(y=x, sr=sr, units='frames')
o_env = librosa.onset.onset_strength(x, sr=sr)
times = librosa.frames_to_time(np.arange(len(o_env)), sr=sr)
onset_times = librosa.frames_to_time(onset_frames)
a=onset_times[1:-1]
b=onset_times[2:-1]
b=np.append(b,[0])
Diff=b-a
print(Diff)
plt.vlines(a, 0, x.max(), color='r', alpha=0.9,
linestyle='--', label='Onsets')
plt.axis('tight')
plt.legend(frameon=True, framealpha=0.75)
plt.show()
I have added the sound files in the below link. One can simulate the file directly. Python Colab Notebook: Link
You can use the Yamnet, it is trained on 512 different sounds with state of the art architecture and data. https://www.tensorflow.org/tutorials/audio/transfer_learning_audio
For the red line it may happen due to the change in the sampling rate. You have to match the sampling rate of the beep.