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Very impressive.
It'd be interesting to see what the lift would be to get encoding & decoding running in webassembly/wasm. Further, it'd be really neat to try to take something like the tflife_model_wrapper[1] and to get it backed by something like tsjs-tflite[2] perhaps even atop for example tfjs-backend-webgpu[3].
Longer run, the web-nn[4] spec should hopefully simplify/bake-in some of these libraries to the web platform, make running inference much easier. But there's still an interesting challenge & question, that I'm not sure how to tackle; how to take native code, compile it to wasm, but to have some of the implementation provided else-where.
[1] https://github.com/google/lyra/pull/89/files#diff-ed2f131a63...
[2] https://www.npmjs.com/package/@tensorflow/tfjs-tflite
[3] https://www.npmjs.com/package/@tensorflow/tfjs-backend-webgp...
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1. Install numpy (pip3 install numpy)
2. Download a bazel binary (https://github.com/bazelbuild/bazel/releases or use package manager)
3. bazel build -c opt :encoder_main
4. bazel-bin/encoder_main --input_path=testdata/sample1_16kHz.wav --output_dir=$HOME/temp --bitrate=3200
Done!