Audio classification in R
Part of the tutorial from my blog poissonisfish.
- Download, unzip and move
mp3/from the Kaggle dataset to your GitHub repo clone
- Make sure all packages listed on top of
- Restart R (recommended) and execute
GPU and multi-threading
The analysis was conducted using an iMac Pro machine with AMD graphics cards and 16 threads. Considering Tensorflow GPU support is exclusive to NVIDIA®, the much less restrictive plaidML framework was used instead, deployed from a Conda environment called
plaidml. Alternative setups including TensorFlow backends (GPU or CPU-supported) can be easily accommodated.
Also, consider changing
0-prepAudio.R as suits your machine specs the best.
To further improve reproducibility, the Keras model object
model.h5 is included to validate the reported accuracy. Additionally,
sessionInfo carries detailed information of the package versions and hardware configuration.
Feel free to report any issues with reproducing the analysis described in the blog.
I want to thank the xeno-canto community for their work in collecting, documenting and sharing this information.