Audio processing in Python with Feature Extraction for machine learning

Python library librosa is a python package for music and audio analysis. It provides the building blocks necessary to create music information retrieval systems.

librosa uses soundfile and audioread to load audio files. Note that soundfile does not currently support MP3, which will cause librosa to fall back on the audioread library.

Library Highlights:
- CoreIO and DSP
- Feature Extraction
- Onset Detection
- Beat and Tempo
- Spectrogram decomposition
- Temporal segmentation
- Sequential modeling
- Viterbi decoding¶

Content Timeline:
-----------------
- (00:00) Video Start
- (00:08) Content Introduction
- (02:27) Python Audio processing resources
- (04:08) Tutorial Source code intro
- (04:40) Tutorial Starts
- (05:18) Royalty free audio
- (05:42) Audio processing with librosa
- (16:25) Beats retrieval from audio
- (18:35) Beats Generation
- (21:01) Features Extraction
- (21:25) Zero Crossing Rate
- (24:37) Spectral Centroid
- (27:30) Spectral Rolloff
- (28:58) MFCCs
- (33:24) Chroma Frequencies
- (36:46) RMS Root-mean-square
- (41:26) Code Push to GitHub
- (42:10) Recap
- (43:29) Credits

Python librosa url:

Source Code used in this example:

Please visit:
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Tags:
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[ritanovitasari]

hello sir, , the tutorial is easy to understand because the explanation is very clear. but I found a problem in this section "'ls' is not recognized as an internal or external command,
operable program or batch file."
please help why this part cannot be recognized. what should I install

[Minos]

👍 Electroacoustic music composer thanks you ! 😀

[drjfilix]

Thanks for your very interesting video!
A question: but if I have to align 2 tracks with different BPM (one 108 and the other 120 bpm) what can I do?
do I raise the first or lower the second? or do I take them both at 119 bpm? but will the beat grid be constant for the 2 files?

[mohamadilhamfahrizisofyan]

when i try the command
plt.figure(figsize=(14, 5))
librosa.display.waveshow(music_array2, alpha=0.1)
plt.vlines(beat_times, -1, 1, color='r')
plt.ylim(-1, 1)

it says : process_plot_var_args' object has no attribute 'prop_cycler'
can you help mee?

[tsegayebiresaw]

Amazing vedio thank you I learn more!! but I want to save the extracted feature to CSV file!! how can I do it? did you provide the souce code?

[ripudamansingh]

thank you sir. the video was very helpful

[bzaz]

Which part of the tutorial do you think would be best for genre determination? I am trying to build a model/application that determines sub genres of Electronic music but might technical music knowledge is limited?

[hesamgh]

thank you for your video, which method is best solution that i can process signal to recognise human voice like hello?

[abugslife]

Hi sir, great video. I learned a lot. Is it possible to use the output from the feature extraction to create AI music composition? Or what else can I do with feature extraction besides creating genre prediction, transcription, and classification programs? I plan on doing feature extraction for my ML project and am looking to see what are the options. Thank you so much

[shubhamkapoor]

Hey the dataset i have is with gz format .how do i work with that ?could you give me pointers

[sandymlgenai]

How can I divide an audio data into several equal sized chunks with padding? ( I'm dividing the data into chunks to apply DCT on every chunk)

[rs]

thanks for the tutorial.
how can i convert to time series data wrt to frames
ex: (time_step, feature_dim)

if my loaded audio data shape is (67032, )
can i reshape it to (12, 5586) #feature size
and then repeat data with 3 time step to create (3, 10, 5586)

I want to use this for lstm model

[harshbhagwani]

this video is enough for audio processing?