the client

...or what the users see

Built with

• Electron
• Node
• JavaScript
• ...and around ~3000 other
  smaller libraries

may be the most "visible" part...

but it's only around 40% of the code

the dashboard

...or what makes anne behave one way or another

The dashboard is:

• The other client-facing part
• What makes Anne "tick"
• Allows us to be very user-centric:
  Their Anne is their own, and they
  get to decide how she behaves.
• Anything can be made a setting,
  and in time, most things will.

The dashboard HAS:

• Settings for every module
• Speech settings
• Fine-grained permissions
• Content / media control

the server bunch

...or the technical mumbo-jumbo that makes it all work together

server-side anatomy

• Amazon services - authentication, data storage, automation, settings (AKA an "API", but that's quite
  innacurate here).
• Miniflux - the server software we use for news.
• Nextcloud - the server software we use for calendars (and potentially much more).

more importantly...

• The thing that makes the dashboard work...
• Which in turn allows the AnneNext client to work.
• In a way, the "heart" of the operation.

the speech stack

...asr, tts, Classifiers and other big words. simplified, i promise :)

TTS - text to speech

• You send it text, it speaks it out
• It can be in various languages
• It can use various voices
• And we aim to make it all configurable
  (via the dashboard)

ASR - automatic speech recognition

• AKA Speech to text (STT)
• You speak to it, and it turns that speech into text
• Also supports various languages
• We also aim to make it configurable via
  the dashboard

the avatar library

• The part that ties ASR, TTS and the AnneNext client together.
• Where ASR brings recognition of phrases, the library makes the client "understand" the phrases - what should be shown on screen, what should Anne say back, etc.
• This is a part of the local AI (Anne comes with multiple AI elements).

A short recap

• AnneNext client reads settings from servers
• Dashboard writes settings to servers
• ASR recognizes speech
• TTS makes text into speech
• The Avatar library makes ASR and TTS
  "talk" to the AnneNext client.

telemetry & AI

...or how we get to know whether a user likes something. and much more!

the data we collect...

• Is completely anonymized*
• We collect it to learn from it:
  • How to improve Anne as a product
  • How to improve Anne for the user
  • Make sure the user is doing good
  • Find ways to make their lives easier

the data we collect...

• Allows caregivers to track well-being
• Track trends across time
• Provide meaningful insights via our AI /
  Analysis tools

the data we collect...

• Is a vital part of the global AI
  (the one that runs on servers)
• Will ultimately allow us to adapt
  Anne to the users needs
• "Seeing" a user's habits, Anne will
  make herself more useful to
  said user
• The more they use her, the better
  she gets