AI in Music Production: How Technology is Changing the Industry
It's hard to believe that just 15 years ago, the music industry was a very different place. With the rise of technology, we have seen huge changes in how music is produced, marketed and consumed. In this blog post, we will take a look at some of the ways that AI has been used in music production and how it is changing the industry.
What is A.I.?
A.I., or artificial intelligence, is a term that is often used in conjunction with machine learning. Machine learning is a process by which computers can learn from data, without being explicitly programmed. This means that they can identify patterns and insights in data that humans would not be able to see. AI has been used in music production for some time now, but how has it helped with music composition and production?
A.I. & Music Throughout History
You might be surprised to find that AI has been used in music production for many years. One of the earliest examples is from 1951, when Alan Turing created computer-generated music for the first time in history. In 1957, composer Lejaren Hiller and mathematician Leonard Isaacson wrote the first musical work ever written by a computer. This was made possible by programming the ILLIAC I (Illinois Automatic Computer).
In 1995, musician David Bowie helped computer programmer Ty Roberts to develop an app called the “Verbasizer”. Verbasizer took literary source material and randomly reordered the words to create new combinations that could be used as lyrics in music.
In recent years, AI has been used to create entire pieces of music. In 2016, Google’s Magenta project called “A.I. Duets”, consisted of a duet between a human and a computer. The project was composed using machine learning algorithms that were trained on a dataset of over 100 hours of piano performance videos.
The "Autotune Effect"
Probably one of the biggest moments, however, was when Autotune came into the scene. Autotune is a software that helps correct pitch in vocal and instrumental performances. It was originally designed to discreetly correct off-key notes, but it soon became popular for its ability to create the “Autotune effect”. This is when a voice is artificially altered to sound like it has been corrected by Autotune, even if it hasn’t been. The effect became so popular that it was used on some of the biggest hits of the 2000s, including Cher’s “Believe” and T-Pain’s “Buy U a Drank (Shawty Snappin')”.
So, how does AI help with music composition and production tasks?
As we have seen, AI can be used to generate entire pieces of music or to help with the composition process. However, AI can also be used in other ways that can help save time and make better decisions.
For example, there are now tools that can help with pitch correction, timing, tempo, tone color and individual notes. Melodyne is a popular tool that uses algorithms to detect and correct these things in vocal and instrumental performances. There are also plugins from Mastering the Mix that can help find and fix errors in your track and give you better sounding music.
Sites like Landr offer an automated mastering service that can give you a mastered track in less than 30 seconds. This is made possible by using machine learning algorithms to analyze your track and make adjustments accordingly.
A.I. and the Future of the Music Industry
More and more tools are being created that use AI to help with music production tasks. As the technology continues to develop, we can only imagine what new and exciting ways AI will be used in music production.
AI is rapidly changing the music industry, and it's hard to say what the future holds. It seems clear that AI will play a big role in music production, and only time, probably a short amount of it, will reveal it soon.
In the meantime, let us know your thoughts on AI in music production and how you think it will be used in the future.
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