You're reading from Hands-On Generative Adversarial Networks with Keras

Product typeBook

Published inMay 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781789538205

Edition1st Edition

Languages

Python

Tools

Keras

Concepts

Neural Networks

Author (1)

Rafael Valle

Natural language generation with GANs

Within the field of Natural language understanding (NLU), Natural language generation is one of the most challenging tasks in machine learning. Broadly speaking, it is easier to estimate the parameters of a discriminative model than a generative model. On Quora (https://www.quora.com/Why-are-generative-models-harder-to-create-than-discriminative-models), Ian Goodfellow gives a good informal explanation that can be generalized to language:

Can you look at a painting and recognize it as being the Mona Lisa? You probably can. That's discriminative modeling. Can you paint the Mona Lisa yourself? You probably can't. That's generative modeling.

The task of modeling language has been approached with rule-based and data-based models, including deep learning. As Ziang Xie has informally explained in his practical guide for neural text...

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Hands-On Generative Adversarial Networks with Keras

Published in: May 2019Publisher: PacktISBN-13: 9781789538205

Author (1)

Rafael Valle

Rafael Valle is a research scientist at NVIDIA focusing on audio applications. He has years of experience developing high performance machine learning models for data/audio analysis, synthesis and machine improvisation with formal specifications. Dr. Valle was the first to generate speech samples from scratch with GANs and to show that simple yet efficient techniques can be used to identify GAN samples. He holds an Interdisciplinary PhD in Machine Listening and Improvisation from UC Berkeley, a Masters degree in Computer Music from the MH-Stuttgart in Germany and a Bachelors degree in Orchestral Conducting from UFRJ in Brazil.
Read more about Rafael Valle

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Author (1)

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