TV VOD EPG information use case

Global use case developed by Aura Platform Team that allows users to get VOD EPG information about the playing content.

Introduction

The TV VOD EPG information use case is a global experience designed and developed by Aura Global Team that allows Telefónica customers to ask Aura about what they are watching on TV at that specific moment using a vocal interface. The use case answers with the name of the TV content being broadcasted.

  • A user interacts with Aura through a normalized video channel
  • She asks about the content currently playing: “What am I watching?”, “What’s on?”
  • Aura recognizes the request and provides back to the channel the information required to answer the request

Find additional information in following the documents:

Specifications

Kernel API

In order to resolve the user’s request, Aura uses Video Contents normalized Kernel API.

Request-response model

TV VOD EPG information use case is adapted to the new request-response normalized model v3.

Available channels

TV VOD EPG information use case could be available for any channel that implements normalized v3 request-response model including TV related data.

Currently, STB channels in BR are already available.

Display features

Currently, the normalized TV VOD EPG information use case includes basic VOD EPG information features for content:

  • VOD EPG information by content

Therefore, the questions could be of this type: “What am I watching?” “Which actors are involved?”

Use case development

The TV VOD EPG information use case development includes these components:

Understanding features

  • TV VOD EPG information use case intent: intent.tv-vod_epg_information

  • TV VOD EPG information use case entities:

Entity Example
ent.device_tv “¿Qué estoy viendo en la tele?”
ent.device_mobile “¿Qué estoy viendo en el móvil?”
ent.device_phone “¿Qué estoy viendo en el teléfono?”

In order to understand users’ requests (utterances), Aura is trained with:

  • NLP expression to recognize the user’s utterance and detect the user’s intention.

Use case logic

Once Aura has recognized the user’s utterance based on NLP components, the use case should be resolved based on: