This project is for adding gmm based recognizers to the vosk api. Items planned:
- Add access to online2-wav-gmm-latgen-faster.
- Add support for regular expression based LMs. Currently we have a session which maintains state for ongoing recognition in streaming fashion. We need another abstraction where we have a connection within which sessions are included. We can then configure the connection with a specific grammar which is used to build HCLG.fst for that connection. Without this, we either need prebuilt HCLG.fst or build it for each session.
Vosk is an offline open source speech recognition toolkit. It enables speech recognition models for 18 languages and dialects - English, Indian English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino, Ukrainian.
Vosk models are small (50 Mb) but provide continuous large vocabulary transcription, zero-latency response with streaming API, reconfigurable vocabulary and speaker identification.
Speech recognition bindings implemented for various programming languages like Python, Java, Node.JS, C#, C++ and others.
Vosk supplies speech recognition for chatbots, smart home appliances, virtual assistants. It can also create subtitles for movies, transcription for lectures and interviews.
Vosk scales from small devices like Raspberry Pi or Android smartphone to big clusters.
For installation instructions, examples and documentation visit Vosk Website.