Synthetic data generation for training of natural language understanding models

US11875787B2 · kind B2 · utility

Assignee

• MICROSOFT TECHNOLOGY LICENSING, LLC · US

Inventors

• Baolin Peng · Bellevue, US
• Chenguang Zhu · Sammamish, US
• Chunyuan Li · Beijing, CN
• Xiujun Li · Seattle, US
• Jinchao Li · Redmond, US
• Nanshan Zeng · Bellevue, US
• Jianfeng Gao · Woodinville, US

Key dates

• Filing date: Oct 11, 2022
• Grant date: Jan 16, 2024
• Expiry date: Oct 11, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G10L15/1822
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

This document relates to machine learning. One example includes a method or technique that can be performed on a computing device. The method or technique can include obtaining a task-semantically-conditioned generative model that has been pretrained based at least on a first training data set having unlabeled training examples and semantically conditioned based at least on a second training data set having dialog act-labeled utterances. The method or technique can also include inputting dialog acts into the semantically-conditioned generative model and obtaining synthetic utterances that are output by the semantically-conditioned generative model. The method or technique can also include outputting the synthetic utterances.