Mimic (version 3 and above) is an offline open source Text-To-speech engine designed by Mycroft A.I. for the eponym Vocal Assistant, that provides multiple voices, available in different languages and variants.
Its neural network is built upon some very good and some not-so-good models, so try some to be sure you get the best one for your need.
Mimic3 doesn't need Mycroft, and it can be run as a simple command line utility, or as a web server with an API.
This TTS bundle makes use of this last feature, so please take note: this openHAB TTS bundle is NOT a standalone, and it requires the Mimic web server to run somewhere (on your openHAB computer, or your network).
You can find more information about the Mimic web server, and how to install it, on the [official documentation](https://mycroft-ai.gitbook.io/docs/mycroft-technologies/mimic-tts/mimic-3#installation).
It supports a subset of SSML, and if you want to use it, be sure to start your text with `<speak>`.
## Configuration
Using your favorite configuration UI to edit **Settings / Other Services - Mimic Text-to-Speech** and set:
- **url** - Mimic URL. Default to `http://localhost:59125`
- **speakingRate** - Controls how fast the voice speaks the text. A value of 1 is the speed of the training dataset. Less than 1 is faster, and more than 1 is slower.
- **audioVolatility** - The amount of noise added to the generated audio (0-1). Can help mask audio artifacts from the voice model. Multi-speaker models tend to sound better with a lower amount of noise than single speaker models.
- **phonemeVolatility** - The amount of noise used to generate phoneme durations (0-1). Allows for variable speaking cadance, with a value closer to 1 being more variable. Multi-speaker models tend to sound better with a lower amount of phoneme variability than single speaker models.
In case you would like to setup these settings via a text file, you can edit the file `runtime.cfg` in `$OPENHAB_ROOT/conf/services` and set the following entries:
The mimic TTS service uses the openHAB TTS cache to cache audio files produced from the most recent queries in order to reduce traffic, improve performance and reduce number of requests.
