A Sound Strategy for Edge AI

Edge Impulse has partnered with ElevenLabs.io to bring synthetic audio generation to their embedded machine learning platform.

Nick Bild
19 days ago β€’ Machine Learning & AI
Synthetic audio generation is available in Edge Impulse (πŸ“·: Edge Impulse)

When considering the present roadblocks that are standing in the way of a more widespread adoption of artificial intelligence (AI)-powered tools, most of us will immediately turn our thoughts to the massive amount of computing resources that are needed to train many cutting-edge algorithms. It is certainly true that the GPUs and energy needed to run them are very costly, and a lot of expertise is needed to operate all of this equipment efficiently as well, but this is by no means the only problem we are facing.

While data collection may not get as much attention, it is every bit as important as the algorithms and the hardware that they run on. After all, machine learning algorithms learn by example. So if there are no sufficiently large and diverse datasets already available in a specific area for a model to learn from, that means it needs to be collected. The collection and annotation of a massive dataset can be time-consuming and expensive enough to sink a project before it even has a chance to get off the ground.

Synthetic data β€” that is, artificially generated data that looks like real data β€” is increasingly being explored by researchers and engineers as a means to lower the barrier to entry in AI development. However, these tools can be challenging to use and integrate into an existing pipeline. Moreover, if the synthetic data is not truly representative of the actual data that the AI system will encounter during operation, it will perform very poorly.

Edge Impulse has a reputation for lowering the barriers to entry into the world of AI development, so it seems fitting that they have recently announced a partnership with ElevenLabs.io to make generating synthetic audio datasets a snap. ElevenLabs.io is a leader in the generative AI space, and these capabilities are now being leveraged to expand audio datasets uploaded to Edge Impulse with additional synthetic examples. One need only give a textual description of the type of sounds that they need, the number of samples to produce, and a few additional parameter values. The synthetic data will automatically appear in Edge Impulse.

Once the data has been generated, one can use the normal Edge Impulse tools to develop a machine learning data analysis pipeline, optimize it, and deploy it to an edge computing device. All without having to do any data collection β€” not a bad deal at all!

While one of the biggest draws of synthetic data is time savings, it should also be noted that the additional data can significantly improve the accuracy of a model. Training an AI algorithm on too small of a dataset is a recipe for a poorly performing system.

Synthetic data generation is available only to Enterprise customers, but if you do not have an Enterprise account, you can still sign up for a free trial to give it a test run. And if you want to see a concrete example of a synthetic dataset being used for a real-world application, be sure to check out the video below.

Nick Bild
R&D, creativity, and building the next big thing you never knew you wanted are my specialties.
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