Suppose you have the following float32 audio representation loaded from any wav file using the librosa package:
import librosa wav_x_path = "any_wav_filepath.wav" wav_source, _ = librosa.load(wav_x_path, sr=16000)
If you then will try to play this audio using, for example, a jupyter notebook, the following snippets sounds in the same way:
from IPython.display import display, Audio display(Audio(wav_source * 2, rate=sampling_rate)) display(Audio(wav_source * 200, rate=sampling_rate)) display(Audio(wav_source / 200, rate=sampling_rate))
Why does it happen that changing audio aptitude (if I correctly understand what wav_source contains audio amplitude), doesn’t affect how the audio sounds?
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Answer
As per the documentation of IPython.display.Audio there is an argument normalize which decides whether to apply automatic scaling of the volume. The default is normalize=True, which is why different amplitude scales is played back at the same level.
Use display(Audio(wav_source * 2, rate=sampling_rate, normalize=False)) and you should be able to hear the difference.