If you just want to download the prebuilt sound files, take a look at the Github releases of this project.
This is a CLI tool for generating Asterisk sound files based of the original transcriptions from the Asterisk Open Source project. The goal is to provide better language support for currently unsupported languages like German. The sound files can be used by any phone software based on Asterisk - like FreePBX. The tool uses the DeepL and ChatGPT API to translate the transcriptions and the Google Text-To-Speech API to generate the sound files. However, the translations still needs some manual work. The tool also converts the generated sound files to the common codecs.
- Install sound files in FreePBX docs/install-sounds-freepbx.md
- How to contribute to this project docs/contribute-to-project.md
- Installed Node.js runtime (atleast Version 20.0.0)
- DeepL account with access to the DeepL API (Free for up to 500.000 characters per month)
- OpenAI account (Not free but really cheap)
- Google Cloud account with access to the Google Text-to-Speech API (Free for up to 1 Mio. characters per month)
- FFmpeg binary for converting the sound files
- Clone the repository
git clone https://github.com/joni1802/asterisk-sound-generator.git
. - Change into the directory
cd asterisk-sound-generator
- Install the Node modules
npm install
- Start the CLI tool
npm run start
- Create a service account for the Google Text to Speech API.
- Create a key pair for the service account and download the JSON file.
- Create a .env file in the root directory of this project.
- Add
GOOGLE_APPLICATION_CREDENTIALS=/path/to/your/key.json
to the .env file.
More details: Using the Text-to-Speech API with Node.js
- Install python.
- Install Coqui TTS by running
pip install TTS
.
More details: Coqui TTS Github Repo
- Create a free DeepL account.
- Generate an API key.
- Create a .env file in the root directory of this project.
- Add
DEEPL_AUTH_KEY=<your deepl api key>
to the .env file.
- Create an OpenAI account.
- Generate an API key.
- Create a .env file in the root directory of this project.
- Add
OPEN_AI_AUTH_KEY=<your deepl api key>
to the .env file.
- Download the prebuilt FFmpeg binaries from an official source. For windows I suggest to download the full build from gyan.dev. This version also contains the needed library for the GSM encoder.
- Copy the ffmpeg binary (executable) to the root directory of this project or add it to the PATH environment variable.