How was this made

Blood, sweat and tears

We have

1. A pipe server (AACSpeakHelperServer.py)

   1. Reads in a config dict from settings.cfg

   2. Creates an object to the TTS Engine and holds it in memory to reduce coldstart time

   3. Speaks using sounddevice (heavily reliant on py3-tts-wrapper)

   4. Handles translation using various translation providers

   5. Communicates via named pipes with clients

2. Client - calling executable (client.py)

   1. You can pass it a config file path and text string

   2. If no text provided, it uses clipboard/pasteboard text

   3. Calls the pipe service to process text

   4. Supports command-line parameters for different configurations

3. CLI Configuration Tool (cli_config_creator.py)

   1. Interactive command-line interface for configuration

   2. Supports all TTS engines and translation providers

   3. Creates and manages settings.cfg files

   4. Replaces the unreliable GUI configuration tool

4. Additional Tools

   1. CreateGridset.py - Creates AAC communication grids

   2. migrate_settings.py - Migrates settings between versions

Configuration Architecture

The application uses a multi-layered configuration approach:

1. settings.cfg - Main configuration file in INI format

   • Contains all TTS engine settings, translation settings, and application preferences

   • Located in %AppData%\Ace Centre\AACSpeakHelper for installed versions

   • Can be customized and distributed to end users

2. config.enc - Encrypted configuration for sensitive data

   • Contains API keys and credentials for cloud services

   • Generated during build process from environment variables

   • Provides fallback credentials when user hasn't configured their own

3. Environment Variables (Development only)

   • Used during development via .envrc files

   • Automatically encrypted into config.enc during build process

4. Command-line Parameters

   • Allow specifying custom configuration files

   • Enable different configurations for different use cases

Technical Implementation

There is a lot of magic to make this work though. This includes

• TTS-Wrapper - a unified wrapper to a range of TTS engines. This is needed as we need a unified way of get_voices and speak, speak_streamed etc
• Sherpa-Onnx - a really nice tooling pipleine to deal with VITS models that run on the edge.
• MMS and Models readied for Sherpa-Onnx - Massive help this work from Meta - and we converted their models for (Sherpa-)Onnx. We made some things on the way like a nice JSON with details on the voices. Commerical Providers: Please note the licence these are under
• QT/QT Threading. We had "fun" with threads. Never again will I do it like this

• Encryption in a github Action of keys and a hideous JSON file from Google. That wasted us a week.

Credits

• Will Wade (original v1, refactoring v2 several times, dealing with encryption, build scripts and generally pulling my hair out)

• Acer Jay Costillo (QT work and refactoring)

• Gavin Henderson - for making the call on baking in creds. I hated that and several times threw the idea out.

• Simon Poole - CTO at Smartbox for making me aware of MMS.

Whats next?

• SAPI Bridge. This is really what is needed. C++ developers - we need your help. See Roadmap