k2
k2 aims to integrate Finite State Automaton (FSA) and Finite State Transducer (FST) into autograd-based platforms such as PyTorch and TensorFlow. This is particularly advantageous for speech recognition, allowing diverse training objectives and joint system optimization. The focus on pruned FSA composition facilitates efficient ASR decoding and training, utilizing a codebase largely in C++ and CUDA to support parallel execution. Progressing towards production, k2 offers Python integration with pybind11 and has speech recognition recipes in related repositories.
