rhino VS larynx

Download pre-trained models: "Porcupine" from Porcupine Wake Word and Video Player Context from Rhino Speech-to-Intent repositories - You can also train a custom models on Picovoice Console.

In order to initialize the voice AI, we’ll need both Porcupine (.ppn) and Rhino (.rhn) model files. Picovoice has made several pre-trained Porcupine and pre-trained Rhino models available on the Picovoice GitHub repositories. For this Barista app, we’re going to use the trigger phrase Hey Barista and the Coffee Maker context.

Get an AccessKey for free from Picovoice Console. You will need it as part of the init function. Also, get the English Parameter for Rhino from GitHub and save it to the public directory. Rhino uses this file as the basis to understand English context (other languages are also supported).

The only viable option that I found that could reliably infer commands from speech is https://github.com/Picovoice/rhino

Unfortunately it is not open source (the GitHub just has binary blobs) and requires an account to log in to generate and download model files, but the accuracy is great and you can use it to send commands to Home Assistant to turn lights on/off etc.

https://github.com/Picovoice/rhino/blob/master/LICENSE sayt it's Apache 2 license

The most exciting thing about Home Assistant's "Year of the Voice", for me, is that it is apparently enabling/supporting @synesthesiam's continued phenomenal contributions to the FLOSS off-line voice synthesis space.

The quality, variety & diversity of voices that synesthesiam's "Larynx" TTS project (https://github.com/rhasspy/larynx/) made available, completely transformed the Free/Open Source Text To Speech landscape.

In addition "OpenTTS" (https://github.com/synesthesiam/opentts) provided a common API for interacting with multiple FLOSS TTS projects which showed great promise for actually enabling "standing on the shoulders of" rather than re-inventing the same basic functionality every time.

The new "Piper" TTS project mentioned in the article is the apparent successor to Larynx and, along with the accompanying LibriTTS/LibriVox-based voice models, brings to FLOSS TTS something it's never had before:

* Too many voices! :)

Seriously, the current LibriTTS voice model version has 900+ voices (of varying quality levels), how do you even navigate that many?![0]

And that's not even considering the even higher quality single speaker models based on other audio recording sources.

Offline TTS while immensely valuable for individuals, doesn't seem to be attractive domain for most commercial entities due to lack of lock-in/telemetry opportunities so I was concerned that we might end up missing out on further valuable contributions from synesthesiam's specialised skills & experience due to financial realities & the human need for food. :)

I'm glad we instead get to see what happens next.

[0] See my follow-up comment about this.

Larynx!

I've had good results with https://github.com/rhasspy/larynx

Larynx is a really good text-to-speech engine

I was able to install 3.7 following this guide. https://github.com/rhasspy/larynx/issues/9

If you've not already encountered them I'd definitely encourage you to check out these Free/Open Source projects too:

* Larynx: https://github.com/rhasspy/larynx/

* OpenTTS: https://github.com/synesthesiam/opentts

* Likely Mimic3 in the near future: https://mycroft.ai/blog/mimic-3-preview/

Larynx in particular has a focus on "faster than real-time" while OpenTTS is an attempt to package & provide common REST API to all Free/Open Source Text To Speech systems so the FLOSS ecosystem can build on previous work supported by short-lived business interests, rather than start from scratch every time.

AIUI the developer of the first two projects now works for Mycroft AI & is involved in the development of Mimic3 which seems very promising given how much of an impact on quality his solo work has had in just the past couple of years or so.

I haven't used it on it's own, but Larynx has worked well for me for Rhasspy