GENERATING CANONICAL FORMS FOR TASK-ORIENTED DIALOGUE IN CONVERSATIONAL AI SYSTEMS AND APPLICATIONS

In various examples, techniques for training and using a task-oriented dialogue system are described. Systems and methods are disclosed for determining, using a prompt model(s) and based at least in part on text data, prompt data representing one or more prompts. Additionally, systems and method are...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Sreedhar, Makesh Narsimhan, Parisien, Christopher
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:In various examples, techniques for training and using a task-oriented dialogue system are described. Systems and methods are disclosed for determining, using a prompt model(s) and based at least in part on text data, prompt data representing one or more prompts. Additionally, systems and method are disclosed for determining, using a language model(s) and based at least in part on the text data and the prompt data, a canonical form associated with the text data. In some examples, the prompt model(s) is trained to generate the prompt data that causes the language model(s) to output the canonical form. Systems and method are further disclosed for using the canonical form to determine at least an intent associated with the text data. A dialogue manager may then use the intent to perform one or more actions associated with the text data.