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whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples. whisper.cpp supports integer quantization of the Whisper ggml models. Quantized models require less memory and disk space and depending on the hardware can be processed more efficiently.

This library is being created as I have a need to do very fast FFTs on low end devices not supporting the NEON instruction set. The Raspberry Pi is an ideal candidate for developing in gcc before porting to JNI for low spec Android devices, hence it's inclusion. Fixed point 16/32 integer FFT library suitable for the Raspberry Pi and Android devices.