Speechcatcher-webgui is a web based GUI for automatic transcription and subtitling engines. It supports speech recognition models like speechcatcher (CPU) and whisper (GPU).

It is recommended to run Speechcatcher-webgui natively on a server or workstation. Espacially if you plan on using GPU acceleration, virtualization will usually make your setup needlessly complicated.

The first step is cloning this repository:

git clone https://github.com/speechcatcher-asr/speechcatcher-webgui

Npm is used for all Javascript dependencies. To install them, simply do:

cd frontend
npm install

Note: currently 'npm run' isn't linked, as speechcatcher-webgui is still in development. The weppage directly references the scripts in the "node_modules/" directory. This will be changed for a production installation at a later stage.

First create a virtual environment for the backend and activate it, then you can install required packages with pip:

cd backend/
virtualenv -p python3.10 backend_env
source backend_env/bin/activate
pip3 install -r requirements.txt

Note: currently we used the integrated flask server for development purposes, but this will be changed to a production server (like gunicorn) at a later stage of this project.

Speechcatcher-webgui uses nginx to serve static content and also uses it to reverse proxy the backend.

In a typical debian/ubuntu based distrbution you can install nginx with:

sudo apt-get install nginx

Then you can copy the sample config file.

cp speechcatcher_nginx_sample.conf /etc/nginx/sites-available/speechcatcher.conf

make some changes to /etc/nginx/sites-available/speechcatcher.conf, at the very least configure the root directory to match your frontend installation. Then make a link:

ln -s /etc/nginx/sites-available/speechcatcher.conf /etc/nginx/sites-enabled/speechcatcher.conf

You can now restart the nginx server:

sudo service restart nginx

When you start the backend server make sure that you are in the correct virtual environment and in the backend directory:

source backend_env/bin/activate
cd backend
python3 speechcatcher_server.py

in a new screen or window, start the rqworker service:

rqworker

On newer versions of Mac OS X you might need to do:

OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES rqworker

So that rqworker doesn't crash on trying to fork.

You should now be able to see and use the webgui on https://localhost/