Making music using new sounds generated with machine learning

Making music using new sounds generated with machine learning

  • March 16, 2018
Table of Contents

Making music using new sounds generated with machine learning

Technology has always played a role in inspiring musicians in new and creative ways. The guitar amp gave rock musicians a new palette of sounds to play with in the form of feedback and distortion. And the sounds generated by synths helped shape the sound of electronic music.

But what about new technologies like machine learning models and algorithms? How might they play a role in creating new tools and possibilities for a musician’s creative process? Magenta, a research project within Google, is currently exploring answers to these questions.

Source: blog.google

Tags :
Share :
comments powered by Disqus

Related Posts

Using AI to match human performance in translating news from Chinese to English

Using AI to match human performance in translating news from Chinese to English

Read More
Using Google Cloud AutoML to Classify Poisonous Australian Spiders

Using Google Cloud AutoML to Classify Poisonous Australian Spiders

Google’s new Cloud AutoML Vision is a new machine learning service from Google Cloud that aims to make state of the art machine learning techniques accessible to non-machine learning experts. In this post I will show you how I was able, in just a few hours, to create a custom image classifier that is able to distinguish between different types of poisonous Australian spiders. I didn’t have any data when I started and it only required a very basic understanding of machine learning related concepts.

Read More
Deep Neural Network implemented in pure SQL over BigQuery

Deep Neural Network implemented in pure SQL over BigQuery

In this post, we’ll implement a deep neural network with one hidden layer (and ReLu and softmax activation functions) purely in SQL. The end-to-end steps for neural network training including the forward pass and back-propagation will be implemented as a single SQL query on BigQuery. As it runs on Bigquery, in effect we are performing distributed neural network training on 100s to 1000s of servers.

Read More