Generating Sound with Neural Networks: Difference between revisions
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= Sound Generation with Deep Learning - Approaches and Challenges = | = Sound Generation with Deep Learning - Approaches and Challenges = | ||
<evlplayer id="player1" w="480" h="360" service="youtube" defaultid="pwV8K9wXY2E" /> | <evlplayer id="player1" w="480" h="360" service="youtube" defaultid="pwV8K9wXY2E" /> | ||
0:00 Intro | 0:00 Intro | ||
0:33 Defining the sound generation task | 0:33 Defining the sound generation task | ||
1:17 Classification of sound generation systems | 1:17 Classification of sound generation systems | ||
2:14 Types of generated sounds | 2:14 Types of generated sounds | ||
3:41 Sound representations | 3:41 Sound representations | ||
4:07 Generation from raw audio | 4:07 Generation from raw audio | ||
7:40 Challenges of raw audio generation | 7:40 Challenges of raw audio generation | ||
10:21 Generation from spectrograms | 10:21 Generation from spectrograms | ||
16:12 Advantages of generation from spectrograms | 16:12 Advantages of generation from spectrograms | ||
18:07 Challenges of generation from spectrograms | 18:07 Challenges of generation from spectrograms | ||
20:26 Can we generate sound with MFCCs? | 20:26 Can we generate sound with MFCCs? | ||
21:26 DL architectures for sound generation | 21:26 DL architectures for sound generation | ||
22:13 Inputs for generation | 22:13 Inputs for generation | ||
24:03 Details about the sound generative system we'll build | 24:03 Details about the sound generative system we'll build | ||
24:44 What's next? | 24:44 What's next? | ||
= Autoencoders Explained Easily= | = Autoencoders Explained Easily= | ||
Revision as of 14:43, 12 December 2021
Generating Sound with Neural Networks
Learn how to generate sound from audio files 🎧 🎧 using Variational Autoencoders.
Sound Generation with Neural Networks - INTRO[edit]
Sound Generation with Deep Learning - Approaches and Challenges[edit]
0:00 Intro 0:33 Defining the sound generation task 1:17 Classification of sound generation systems 2:14 Types of generated sounds 3:41 Sound representations 4:07 Generation from raw audio 7:40 Challenges of raw audio generation 10:21 Generation from spectrograms 16:12 Advantages of generation from spectrograms 18:07 Challenges of generation from spectrograms 20:26 Can we generate sound with MFCCs? 21:26 DL architectures for sound generation 22:13 Inputs for generation 24:03 Details about the sound generative system we'll build 24:44 What's next?
Autoencoders Explained Easily[edit]
How to Implement Autoencoders in Python and Keras - The Encoder[edit]
How to Implement Autoencoders in Python and Keras - The Decoder[edit]
Building and Training an Autoencoder in Keras + TensorFlow + Python[edit]
Saving the Autoencoder in Keras[edit]
Generation with AutoEncoders: Results and Limitations[edit]
From Autoencoders to Variational Autoencoders: Improving the Encoder[edit]
From Autoencoders to Variational Autoencoders: Improving the Loss Function[edit]
How to implement a Variational AutoEncoder in Python and Keras[edit]
Preprocessing Audio Datasets for Machine Learning[edit]
Training a VAE with Speech Data in Keras[edit]