alphacep/vosk-api

Vosk is an open source speech recognition toolkit that runs offline, meaning it does not need to send audio to a cloud service. According to the README it covers more than 20 languages and dialects, including English, Indian English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino, Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech, and Polish. The authors say more are on the way. The models that do the recognition work are small, around 50 megabytes, but the README says they still handle continuous transcription with a large vocabulary. The streaming API responds with no waiting, the vocabulary can be reconfigured, and the toolkit can also identify which speaker is talking. These claims come directly from the project's own description, so a reader should evaluate them on their own data. Because Vosk is a library rather than a finished app, you reach it through bindings in different programming languages. The README lists Python, Java, Node.js, C#, C++, Rust, and Go, with others available. The repository description adds Android and iOS as supported platforms, alongside Raspberry Pi and servers, so the same toolkit can be dropped into a phone app or a back-end service. The use cases the README highlights are chatbots, smart home appliances, and virtual assistants, plus subtitle generation for movies and transcription of lectures and interviews. It scales from a single Raspberry Pi or Android phone up to large clusters of machines, which means the same model files work in very different environments. The README itself is short. For install instructions, code examples, and full documentation it points to the project website at alphacephei.com/vosk. The topics on the repository mention ASR (automatic speech recognition), deep learning, deep neural networks, and comparisons to DeepSpeech, Google Speech-to-Text, and Kaldi, which gives a sense of where this project sits in the speech recognition landscape.