#Flashlight

Explore the next step in speech recognition development with wav2letter's integration into Flashlight ASR. Access pivotal pre-consolidation resources and use detailed recipes for reproducing significant research models like ConvNets and sequence-to-sequence architectures. Utilize data preparation tools, confirm reproducibility with Flashlight 0.3.2, and connect with the dynamic wav2letter community. This MIT-licensed project offers innovative solutions for both supervised and semi-supervised speech recognition.

Flashlight is a versatile C++ library designed by top AI researchers for machine learning, providing significant internal modifiability and efficient performance. It features a core of under 10 MB, utilizing modern C++ and the ArrayFire library for optimal performance in areas like speech recognition, image classification, and more. It supports both CUDA and CPU backends, offers high configurability, and integrates seamlessly with vcpkg and Docker setups, making it an ideal choice for researchers interested in flexible experimentation.