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This is a project aiming to create my own neural network inference library.
This project has two parts, one is the parser part which has not yet been made public and this is the inference part which has been made public but I considered not done, I will try to spend time to make it much better.
This program here utilized the Dual-signal Transformation LSTM Network(DTLN) to denoise audio comming in from a microphone(with miniaudio full duplex)
This part is made public first because it can produce its own goal, and I must push my Medium story immediately so I rushed this out.
Project structure
Parser
The parser is not yet made public, it's purpose is to parse an ONNX model file and create a header file similar to "model1.h", "model1.c", "model2.h", "model2.c".
The generated header and source file contain the node description and weight of the file, it is then added into the inference part.
It's dependency is protobuf.
Inference
This project.
It runs the DTLN model by using the pair of files created by the parser.
There is still a lot of optimization and making it conform to coding guidelines should be done.