Featurization of Conversations

These docs are for version 1.x of Rasa Open Source.

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• Tutorial: Rasa Basics
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API Reference

• Action Server
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• Rasa SDK
• Events
• Tracker
• Tracker Stores
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• Training Data Importers
• Featurization of Conversations
• TensorFlow Configuration
• Migration Guide
• Rasa Open Source Change Log

Migrate from (beta)

• Dialogflow
• Wit.ai
• LUIS
• IBM Watson

Reference

• Glossary

Versions

viewing: 1.10.6

Featurization of Conversations

In order to apply machine learning algorithms to conversational AI, we need to build up vector representations of conversations.

Each story corresponds to a tracker which consists of the states of the conversation just before each action was taken.

State Featurizers

Every event in a tracker’s history creates a new state (e.g., running a bot action, receiving a user message, setting slots). Featurizing a single state of the tracker has a couple of steps:

1. Tracker provides a bag of active features:

   • features indicating intents and entities.
   • features indicating which slots are currently defined.
   • features indicating the results of any API calls stored in slots.
   • features indicating what the last action was.

2. Convert all the features into numeric vectors:

   We use the X, y notation that’s common for supervised learning.

   The target labels correspond to actions taken by the bot.

   To convert the features into vector format, there are different featurizers available:

   • BinarySingleStateFeaturizer creates a binary one-hot encoding.
   • LabelTokenizerSingleStateFeaturizer creates a vector based on the feature label.

Tracker Featurizers

It’s often useful to include a bit more history than just the current state when predicting an action. The TrackerFeaturizer iterates over tracker states and calls a SingleStateFeaturizer for each state. There are two different tracker featurizers:

1. Full Dialogue - creates numerical representation of stories.
2. Max History - creates an array of previous tracker states for each bot action or utterance.