How AI Sound Synthesis Works

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Artificial intelligence is changing software sound synthesis (learn more) in big ways. It’s causing people to rethink how they’ve always done things, and it could change the future of the industry.

As AI gets better, it’s starting to be used more. It’s not just making old ways of doing things faster, but it’s also creating new ways to create and change sounds.

Sound designers might find this a tricky situation. Using AI could lead to finding new sounds. But, it also makes people wonder about the role of human touch and skill in the art.

AI can be both a tool and a partner in sound design. This means thinking about how they work and what these new tools mean.

How Artificial Intelligence Works

Artificial Intelligence copies how the human mind works. It uses a bunch of rules and math (i.e. algorithms) and different ways for a machine to learn. Just like the human brain, it can think, make plans, understand things, and work with human language.

The two main components of AI are Machine Learning and Deep Learning.

Machine Learning involves feeding the AI system with vast amounts of data and letting it learn patterns and make decisions based on that, while Deep Learning involves neural networks with several layers to enable learning and decision making.

To really understand AI requires a deep understanding of computer sciences – programming languages, etc.

How AI is Applied to Sound Synthesis

AI-based sound synthesis is mainly about creating new sounds that don’t exist in the real world or recreating existing sounds.

This process involves the use of AI algorithms that understand and learn the characteristics of sound and then generate new sounds based on those learned patterns.

One of the most common ways AI is used in sound synthesis is through a type of neural network called a Convolutional Neural Network (CNN).

A CNN is programmed to learn on its own. It adapts and picks up patterns in sounds and gradually learns to understand layers of features in these sounds.

Another technique is through Generative Adversarial Networks (GANs), which consist of two neural networks – a generator and a discriminator.

The generator creates sounds, and the discriminator evaluates them based on real-world examples. The generator learns and improves over time to produce sounds that are nearly indistinguishable from real-world sounds.

Diagram of how a GAN works
Image from BBC Science Focus

AI’s Role in Sound Evolution

AI is quickly changing the world of sound design. It’s bringing new tools and methods that are changing how we make, change, and hear sound.

These new changes are making work easier and are also opening up many new creative options that we once thought were impossible. AI and sound design are coming together in a way that’s changing the industry, thanks to new technology that’s pushing the limits of sound art.

AI tools can now accurately separate voices, smoothly remove unwanted noise, and even predict and match sound to silent videos in a very realistic way.

Plus there are all the AI-generated songs – some of which sound like terrible music right now, and others that are realistic emulations of the voices of mega pop stars.

These future changes show how powerful AI is and how it can change the world of sound.

Machine learning tools like ARTIST and Nsynth, shows how AI is changing sound synthesis. This isn’t just an upgrade to old methods; it’s a completely new way of thinking about, making, and sharing sound, marking a new era in sound.

Revolutionary AI Sound Applications

AI is obviously changing the world of sound design in amazing ways.

But it’s not just about new tech making things easier. It’s also about changing how we think about creativity and technology.

As AI gets better, it’s going to let sound designers do things they could only dream of before. It’s a game-changer for the world of sound.

This isn’t just a small step forward – it’s a huge leap into a new world of creativity and innovation.

Below are some of the most revolutionary applications of artificial intelligence to the world of sound.

Learning Models in Audio AI

AI has changed the way we design sound. This change is due to learning models in AI.

These models work like the human brain. They spot patterns and process information in a different way. This is what helps machines to recognize sounds accurately.

AI also uses something called machine learning. This helps machines get better at tasks like voice synthesis and speech recognition. Machines can learn from a lot of data, making them work better without having to be programmed for each new sound.


ARTIST (Artificial Intelligence for Sound Design) is a machine learning-based tool developed for sound synthesis and design. It is a result of a research project that aims to create new sounds by combining and transforming existing ones.

ARTIST uses a deep learning approach, specifically a variant of autoencoder, to learn the characteristics of different sounds, and then synthesizes new sounds based on the learned models.

ARTIST has been used in sound synthesis and design in various ways. Here are a few examples:

  1. Sound Morphing: ARTIST has been used to morph between different sounds, creating smooth transitions and complex soundscapes that would be difficult to achieve using traditional sound design techniques.
  2. Sound Enhancement: It can also be used to enhance the quality of sounds, such as removing noise or increasing the sharpness of a sound.
  3. Creative Sound Design: ARTIST can be used to create entirely new sounds, which can be used in various fields such as music production, film scoring, and video game design.
  4. Sound Recognition: It can be used to recognize and classify sounds based on the learned models, which can be useful in many applications, such as automatic music genre classification, sound effect recognition, etc.
A Hand using a touchscreen tool to control the NSynth engine
Google Brain’s NSynth Super


NSynth, short for Neural Synthesizer, is a machine learning based project developed by the Magenta team of Google Brain. It is a tool that uses deep neural networks to learn the characteristics of sounds, and then create a completely new sound based on these characteristics.

The way NSynth works is by analyzing the individual qualities of each note that comes from thousands of different instruments. The system then uses this data to generate a mathematical vector for each note.

This vector can then be used to create new sounds based on the characteristics of the original sounds, resulting in a completely new sound that can’t be achieved with traditional sound synthesis.

NSynth has been used in a variety of ways. First and foremost, it has been used to create new sounds for musical composition. Because of its ability to generate entirely new sounds, it gives musicians and artists a new tool to create unique music.

NSynth has been used in a device called the NSynth Super, which is an open source experimental instrument that can generate new sounds using the NSynth technology.

It also provides a new way to analyze and understand the nature of sounds, which can help to develop new sound synthesis methods.

How AI Can Help Artists

When thinking about technical sound design, we must keep in mind the small but powerful effect of different audio processing methods.

As we start to use AI in these various synthesis methods, it’s very important to make sure the algorithms work as well as they can. Creating smart algorithms that can handle audio data well is a key part of modern sound design.

Once these algorithms are set up right, they can do regular tasks automatically, find new ways of looking at sound, and even guess what the sound designer might need next.

Lastly, checking the quality of the sound design work is a very important step. It makes sure the final sound meets the high standards clients and audiences expect.

AI tools can help in this step by checking the audio for mistakes or parts that don’t match up. This makes the workflow smoother and lets sound designers spend more time on the fun, creative parts of their projects.

AI’s Double Edged Sword

Artificial intelligence is becoming a key helper in creative sound design.

Sound designers can work together with AI to make sounds we’ve never heard before. This mix of computer accuracy and human creativity can make music better in ways we couldn’t imagine before.

However, working with AI also brings ethical issues that need thinking about. As AI can make complicated soundscapes, questions about who made it and if it’s original come up.

Further AI may be difficult to reconcile with intellectual property rights as a whole. Voices and styles will be able to be mimicked rather easily using artificial intelligence. We’ve already seen examples of these in the wild.

It is important to make sure AI is an ethical partner in sound design.

The future of sound design is in this teamwork between AI and people. Together, they both push the boundaries of sound but also cause unexpected issues and problems to arise.

We need to think deeply and tread carefully when it comes to the integration of AI in the creative fields of music and sound.

What to Do Next

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