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Vosk is a speech recognition toolkit. The best things in Vosk are:

1. Supports 9 languages - English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese. More to come.
2. Works offline, even on lightweight devices - Raspberry Pi, Android, iOS
3. Installs with simple pip3 install vosk
4. Portable per-language models are only 50Mb each, but there are much bigger server models available.
5. Provides streaming API for the best user experience (unlike popular speech-recognition python packages)
6. There are bindings for different programming languages, too - java/csharp/javascript etc.
7. Allows quick reconfiguration of vocabulary for best accuracy.
8. 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 [email protected].

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-small-en-us-0.3.zip
mv alphacep-model-small-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-small-en-us-0.3.zip
mv alphacep-model-small-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-small-en-us-0.3.zip
mv alphacep-model-small-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 [email protected]
• Join our group dedicated to speech recognition on Telegram @speech_recognition
• Join Wechat group for discussion in Chinese