Vosk is a speech recognition toolkit. The best things in Vosk are:
- Supports 9 languages - English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese. More to come.
- Works offline, even on lightweight devices - Raspberry Pi, Android, iOS
- Installs with simple
pip3 install vosk - Portable per-language models are only 50Mb each, but there are much bigger server models available.
- Provides streaming API for the best user experience (unlike popular speech-recognition python packages)
- There are bindings for different programming languages, too - java/csharp/javascript etc.
- Allows quick reconfiguration of vocabulary for best accuracy.
- Supports speaker identification beside simple speech recognition.
Android build
cd android
gradle build
Please note that medium blog post about 64-bit is not relevant anymore, the script builds x86, arm64 and armv7 libraries automatically without any modifications.
For example of Android application using Vosk-API check https://github.com/alphacep/kaldi-android-demo project
iOS build
Available on request. Drop as a mail at contact@alphacephei.com.
Python installation from Pypi
The easiest way to install vosk api is with pip. You do not have to compile anything.
We currently support the following platforms:
- Linux on x86_64
- Raspbian on Raspberry Pi
- Linux on arm64
- OSX
- Windows
Make sure you have newer pip and python3:
- Python version: 3.5-3.8 (Linux), 3.6-3.7 (ARM), 3.8 (OSX), 3.8 (Windows)
- pip version: 19.0 and newer.
Uprade python and pip if needed. Then install vosk on Linux/Mac with a simple command
pip3 install vosk
Please note that some platforms are not fully supported by pip, for example you have install on arm64 from released wheels:
pip3 install https://github.com/alphacep/vosk-api/releases/download/0.3.7/vosk-0.3.7-cp37-cp37m-linux_aarch64.whl
Also please note that Vosk requires libgfortran on some Linux builds which might be missing, you might need to install libgfortran with a package manager.
In case of trouble installing, check the following
- python3 --version
- pip3 --version
- pip3 -v install vosk
Websocket Server and GRPC server
We also provide a websocket server and grpc server which can be used in telephony and other applications. With bigger models adapted for 8khz audio it provides more accuracy.
The server is installed with docker and can run with a single command:
docker run -d -p 2700:2700 alphacep/kaldi-en:latest
For details see https://github.com/alphacep/vosk-server
Compilation from source
If you still want to build from scratch, you can compile Kaldi and Vosk yourself. The compilation is straightforward but might be a little confusing for newbie. In case you want to follow this, please watch the errors.
Kaldi compilation for local python, node and java modules
git clone -b lookahead --single-branch https://github.com/alphacep/kaldi
cd kaldi/tools
make
install all dependencies and repeat make if needed
extras/install_openblas.sh
cd ../src
./configure --mathlib=OPENBLAS --shared --use-cuda=no
make -j 10
Kaldi compilation on OSX
The process is about the same except you don't really need OpenBLAS. On OSX kaldi uses Accelerate framework.
Python module build
Then build the python module
export KALDI_ROOT=<KALDI_ROOT>
cd python
python3 setup.py install --user --single-version-externally-managed --root=/
Running the example code with python
Run like this:
cd vosk-api/python/example
wget https://alphacephei.com/kaldi/models/vosk-model-small-en-us-0.3.zip
unzip alphacep-model-android-en-us-0.3.zip
mv alphacep-model-android-en-us-0.3 model
python3 ./test_simple.py test.wav
To run with your audio file make sure it has proper format - PCM 16khz 16bit mono, otherwise decoding will not work.
You can find other examples of using a microphone, decoding with a fixed small vocabulary or speaker identification setup in python/example subfolder
Java example API build
Or Java
cd java && KALDI_ROOT=<KALDI_ROOT> make
wget https://alphacephei.com/kaldi/models/vosk-model-small-en-us-0.3.zip
unzip alphacep-model-android-en-us-0.3.zip
mv alphacep-model-android-en-us-0.3 model
make run
C# build
Or C#
cd csharp && KALDI_ROOT=<KALDI_ROOT> make
wget https://alphacephei.com/kaldi/models/vosk-model-small-en-us-0.3.zip
unzip alphacep-model-android-en-us-0.3.zip
mv alphacep-model-android-en-us-0.3 model
mono test.exe
Models for different languages
For information about models see the documentation on available models.
Contact Us
If you have any questions, feel free to
- Post an issue here on github
- Send us an e-mail at contact@alphacephei.com
- Join our group dedicated to speech recognition on Telegram @speech_recognition
- Join Wechat group for discussion in Chinese
