I also worked on adding rules for the same. In the earlier blog, I mentioned the stories and showed snippets for the stories of start/stop voice commands. To handle this, I created a suitable request and response model schema along with the required stories and rules. Rasa should consider these requirements and respond to the user as necessary, such as “Please select a car before recording the track”. It is necessary to check a number of prerequisites before beginning track recording. The NLP/NLU part will only identify a specific entity and provide responses with data to some extent. Added stories for start, stop, and unspecified action for track recordingĭevelop a request and response schema for voice commandsĪs discussed in the mid-term blog, recognizing the user’s intent via NLP/NLU is not enough to integrate voice commands in the application.Added training data for starting/stopping track recording.Added pipeline configurations to the model. Further implementation details of this goal are covered as part of the mid-term blog. To achieve this, we used Rasa Open Source to recognize the intent and run custom actions to perform voice commands in enviroCar. The third goal was to use natural language processing/natural language understanding (NLP/NLU) to recognize the user’s intent and carry out the appropriate action in the enviroCar App.
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