Misc. functionality

Audio format conversion

You can convert you audio in .mp4, .mp3, .m4a and .aac to .wav. This will allow you to use audio feature generation and classification functionalities.

In order to convert your audios, the following code sample can be used.

from pyAudioProcessing.convert_audio import convert_files_to_wav

# dir_path is the path to the directory/folder on your machine containing audio files
dir_path = "data/mp4_files"

# simply change audio_format to "mp3", "m4a" or "acc" depending on the format
# of audio that you are trying to convert to wav
convert_files_to_wav(dir_path, audio_format="mp4")

# the converted wav files will be saved in the same dir_path location.

Audio cleaning

To remove low-activity regions from your audio clip, the following sample usage can be referred to.

from pyAudioProcessing import clean

clean.remove_silence(
	      <path to wav file>,
               output_file=<path where you want to store cleaned wav file>
)

Audio visualization

To see time-domain view of the audios, and the spectrogram of the audios, please refer to the following sample usage.

from pyAudioProcessing import plot

# spectrogram plot
plot.spectrogram(
     <path to wav file>,
    show=True, # set to False if you do not want the plot to show
    save_to_disk=True, # set to False if you do not want the plot to save
    output_file=<path where you want to store spectrogram as a png>
)

# time-series plot
plot.time(
     <path to wav file>,
    show=True, # set to False if you do not want the plot to show
    save_to_disk=True, # set to False if you do not want the plot to save
    output_file=<path where you want to store the plot as a png>
)