AssistantJS

"develop ambitious platform-agnostic voice applications with ease"

About me

  • Toni, 24 years old
  • Working as conversational services architect @ Web Computing in Münster
  • Masterthesis about platform-agnostic voice applications
  • Maintainer of AssistantJS

Today's agenda

1. Basics of conversational applications

2. Hands on: Developing our own caring bot

Basics of

conversational applications

Participating components

Our Job

?

The assistant's backend

ASR = Automatic speech recognition

NLU = Natural language understanding

NRE = Named entity recognition

DM = Dialogmanager

?

NLU buzzwords

Utterance: Exemplary statements leading to intent

 

Intent: Intention of a user's voice query

 

Entity: Variables of a statement (e. g. "How do I get to the [train station]?")

Participating components

Intents and states

Developing a carebot

1) Generate new application

2) Integrate Alexa

3) Add first intents

4) Add response variations

5) Add general intents

6) Add second state

7) Add entity validation

8) Add google assistant

Additional features

  • Platform-specific tests with Jasmine
  • Strategy-based authentication
  • Rich module-dependent logging

Conclusion

Our app's capabilities

  • App starts the conversation with "How was your day?" and understands goodDayIntent and badDayIntent
  • If the user has had a bad day, app asks for reason
  • User is able to blame a mean colleague, app plots the revenge
  • App detects if user did not mention the name of the mean colleague and follows up for it.
  • App varies all given responses automatically and is multi-language-capable
  • App works with Amazon Alexa and Google Assistant - on all devices

STAR BUTTON

(a.k.a. "the one to press")

AssistantJS repository

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AssistantJS

By Antonius Ostermann

AssistantJS

A brief overview of AssistantJS, including a "hands on" tutorial to create a voice app using AssistantJS. (http://assistantjs.org)

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