As an Ada enthusiast, I’ve always wanted to try my hand at machine learning, but was discouraged by the fact that Python seemed to be the only language supported by most ML frameworks. However, I recently discovered the Open Neural Network Exchange (ONNX) format, a universal way of representing machine learning models, and a library for working with it. One thing I love about ONNX is that there are many pre-trained models available for various applications.
I was excited to find out that I could use Ada to load and make inference with ONNX models, so I created a binding for the ONNX Runtime library and wrote a couple of example programs. These examples include handwriting digit recognition and English speech synthesis. Unfortunately, the speech synthesis example required converting text to phoneme sequences, which I haven’t yet implemented in Ada, in order to keep the examples compact.
Overall, I’m thrilled to have been able to dive into the world of machine learning using my favorite programming language, and I hope that other Ada enthusiasts will find this information useful. If anyone is interested in trying it out for themselves, I’m happy to share my code and provide more information on how to get started with Ada and ONNX.
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