Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.

Run (Development Environment)

Enable venv:

python3.9 -m venv venv
source venv/bin/activate

Install poetry with following command:

pip3 install poetry==1.2.0

Install packages:

poetry install

Starting the Webservice:

poetry run whisper_asr

Quick start

After running the docker image or poetry run whisper_asr interactive Swagger API documentation is available at localhost:9000/docs

Simply upload your sound file and choose either translate or transcribe. Optionally you can provide the language of the input file, otherwise it will be automatically detected.

Build

Run

poetry build

Configuring the Model

export ASR_MODEL=base

Docker

Build Image

docker build -t whisper-asr-webservice .

Run Container

docker run -d -p 9000:9000 whisper-asr-webservice
# or
docker run -d -p 9000:9000 -e ASR_MODEL=base whisper-asr-webservice

TODO

Detailed README file
Github pipeline
Unit tests
CUDA version of Docker image