Artificial intelligence (AI) has been used in the music industry for decades to enhance various aspects of music creation, such as composition, performance, sound design, mixing and mastering. In recent years, AI has become more accessible, powerful and versatile, thanks to the advances in machine learning, deep learning and neural networks. These technologies enable AI to learn from large amounts of data and generate new data based on it, such as text, images, video and sound.
In this article, we’ll look at some of the ways that AI is transforming music production in 2023 and how music producers can benefit from using AI tools in their creative process.
Automating workflows
One of the most obvious paradigm shifts in terms of AI and music production has been AI’s ability to automate workflows. Gone are the days when music producers waste time on repetitive tasks, such as finding samples, tuning vocals, editing audio, applying effects and adjusting levels. Nowadays, producers can free up their time by using AI tools that can perform these tasks automatically and efficiently.
For example, MusicLM is a browser-based AI music generator that can turn text descriptions into audio clips. It uses a neural network model called Music Transformer to learn from millions of songs and generate new music based on the user’s input. MusicLM can be used to create royalty-free samples, melodies, loops and beats for any genre or style. Producers can simply type in what they want to hear and download the audio files for further processing.
Another example is Riffusion, an AI-powered plugin that can generate guitar riffs based on the user’s preferences. Riffusion uses a deep learning algorithm called RiffNet to analyse thousands of guitar riffs and create new ones that match the user’s criteria, such as tempo, key, genre and mood. Riffusion can be used to create realistic and original guitar parts for any song or project.
AI-generated instruments and vocals
Another way that AI is transforming music production is by creating new instruments and vocals that can be used in music making. These are not just synthesised sounds or samples, but rather novel sounds that are generated by AI models that learn from real recordings of instruments and vocals.
For instance, MusicGen is an AI platform that can generate realistic instrument sounds based on the user’s input. MusicGen uses a generative adversarial network (GAN, a type of machine-learning model) to learn from thousands of instrument samples and create new ones that sound authentic and natural. MusicGen can be used to create custom instrument sounds for any genre or style.
Similarly, Vocaloid is an AI software that can generate synthetic vocals based on the user’s input. Vocaloid uses a vocal synthesis engine that can produce human-like singing voices based on parameters such as pitch, timbre, expression and lyrics. Vocaloid can be used to create vocal tracks for any song or project. Look up Hatsune Miku – if you are brave.
Music composition tools
Another way that AI is transforming music production is by providing music composition tools that can assist or inspire producers in creating new music. These are not just random generators or presets, but rather intelligent systems that can understand musical structure, harmony, melody and style.
For example, AIVA is an AI platform that can compose emotional soundtracks for ads, video games or movies. AIVA uses a deep neural network called AIVA-Net to learn from thousands of classical music pieces and compose new ones based on the user’s input. AIVA can be used to create original and expressive music for any scenario or mood. Another example is MuseNet, an AI platform that uses GPT-3 to learn from millions of songs and generate new ones based on the user’s input. MuseNet can be used to create diverse and complex music for any genre or style.
Optimize your mix and master
Another way that AI is transforming music production is by optimizing the mix and master of your tracks. These are not just automatic presets or algorithms, but rather adaptive systems that can analyse your tracks and provide feedback and suggestions on how to improve them.
For example, LANDR is an AI platform that can master your tracks online. LANDR uses a machine learning algorithm called LANDR-Net to learn from thousands of mastered tracks and master your tracks based on your preferences. LANDR can be used to enhance the loudness, clarity and balance of your tracks for any platform or format.
Another example is iZotope Neutron 3, an AI-powered plugin that can mix your tracks automatically. Neutron 3 uses a machine learning algorithm called Mix Assistant to analyse your tracks and create a custom mix based on your goals. Neutron 3 can be used to improve the cohesion, balance and clarity of your tracks for any genre or style.
AI is another tool in the toolbox
AI is transforming music production in 2023 by automating workflows, generating instruments and vocals, providing composition tools and optimizing the mix and master of your tracks. These AI tools can help music producers save time, enhance creativity, improve quality and expand possibilities. However, AI is not a replacement for human creativity or skill, but rather a complement and a collaborator. Music producers should use AI tools as a means to express their vision and voice, not as a shortcut or a substitute.
What do you think? Are you already using AI tools in your musical workflow? Let us know which in the comments!