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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....

Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to...

Software for speech recognition in English & Polish languages. Basic versions of SkryBot: 1. SkryBot Home Speech (English Language) - https://sourceforge.net/projects/skrybotdomowy/files/ReleasesEnglish/InstalatorSkryBotHomeSpeechDemo-2.6.9.18117.exe/download 2. SkryBot DoMowy (Polish Language) - https://sourceforge.net/projects/skrybotdomowy/files/ReleasesPolish/InstalatorSkryBotDoMowyDemo-2.4.9.18117.exe/download More...

Arabisc is speaker independent large vocabulary continuous speech recognizer for Arabic language released under GNU license.It is also a collection of open source tools that allows researchers and developers to build speech recognition systems for Arab

Scalable Language API (SLAPI) The most comprehensive architecture for conversational natural-language applications including speech recognition/synthesis, semantics, & machine translation. Used on Android & other mobile app platforms.

VoxForge collects user-submitted speech audio files for the creation of Acoustic Models for Free and Open Source Speech Recognition Engines such as HTK, Julius, ISIP and Sphinx.

This project will show how to implement the Hidden Markov Model approximations of Voice Recognition into embedded and low power systems.