kaldi-asr/kaldi

Kaldi is a speech recognition toolkit, software that converts spoken audio into text. It is aimed at researchers and engineers working on automatic speech recognition (ASR) problems and is one of the established toolkits in the field for building and experimenting with speech recognition systems. The project also covers speaker identification and speaker verification, which involves determining who is speaking rather than what they said. The toolkit is written primarily in C++ and is designed to run on UNIX-based systems including various Linux distributions, macOS (Darwin), and Cygwin, with separate Windows installation instructions also available. It can take advantage of CUDA-capable GPUs for faster processing. Kaldi includes example system builds (called "egs") that let you run complete speech recognition pipelines on standard datasets to get started. It supports cross-compilation to other platforms including Android and Web Assembly (for in-browser execution using the emscripten toolchain). The project provides documentation on its own website covering both usage and the underlying techniques, along with a Doxygen code reference for developers. Community support is available through mailing lists for both users and developers. Contributors are expected to follow the Google C++ Style Guide with a few project-specific exceptions noted in the documentation.