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Arham-Abbas / pENC

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pENC is a fast, hybrid C++/Python toolkit for parallel audio feature extraction and classification. It uses OpenCL (GPU) and Cython (CPU) for accelerated MFCC extraction, supports batch processing, and integrates with scikit-learn for machine learning. Ideal for research and large-scale audio analysis.

python machine-learning cmake research cpp signal-processing opencl cython scikit-learn parallel-computing feature-extraction gpu-acceleration mfcc clfft audio-processing
  • Updated May 26, 2025
  • C++

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