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1
Intro
2
THIS TALK
3
APPLICATIONS
4
DIGITAL SOUND PRIMER
5
AUDIO MIXTURES
6
AUDIO ACQUISITION
7
DIGITAL SOUND REPRESENTATION
8
SPECTROGRAM
9
PRACTICAL EXAMPLE
10
URBANSOUNDSK
11
MEL-FILTERS
12
NORMALIZATION
13
CONVOLUTIONAL NEURAL NETWORK
14
AGGREGATING ANALYSIS WINDOWS
15
DEMO
16
ENVIRONMENTAL SOUND CLASSIFICATION ON
17
TIPS AND TRICKS
18
DATA AUGMENTATION
19
TRANSFER LEARNING FROM IMAGES
20
AUDIO EMBEDDINGS
21
ANNOTATING AUDIO
22
SUMMARY
23
MORE LEARNING
24
QUESTIONS
25
TAGGING
Description:
Explore audio classification using machine learning in this 43-minute EuroPython Conference talk by Jon Nordby. Dive into the world of sound analysis, learning how to convert audio into spectrograms and apply convolutional neural networks for classification tasks. Discover practical applications in speech recognition, music analysis, medical diagnostics, manufacturing quality control, and animal behavior studies. Gain hands-on experience with Keras and TensorFlow frameworks, and learn valuable techniques for achieving usable results with limited data, including transfer learning, audio embeddings, and data augmentation. Covering topics from digital sound representation to environmental sound classification, this talk provides a comprehensive overview of audio classification techniques, suitable for those with a basic understanding of machine learning and digital sound.

Audio Classification with Machine Learning

EuroPython Conference
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