公开(公告)号：US20230401445A1

公开(公告)日：2023-12-14

申请号：US18457708

申请日：2023-08-29

Applicant: Microsoft Technology Licensing, LLC

Inventor： Dilek Z. Hakkani-Tur ,  Asli Celikyilmaz ,  Yun-Nung Chen ,  Li Deng ,  Jianfeng Gao ,  Gokhan Tur ,  Ye Yi Wang

IPC: G06N3/08 ,  G10L15/16 ,  G10L15/22 ,  G10L15/18 ,  G06N3/044

CPC classification number: G06N3/08 ,  G10L15/16 ,  G10L15/22 ,  G10L15/1822 ,  G06N3/044

Abstract: A processing unit can train a model as a joint multi-domain recurrent neural network (JRNN), such as a bi-directional recurrent neural network (bRNN) and/or a recurrent neural network with long-short term memory (RNN-LSTM) for spoken language understanding (SLU). The processing unit can use the trained model to, e.g., jointly model slot filling, intent determination, and domain classification. The joint multi-domain model described herein can estimate a complete semantic frame per query, and the joint multi-domain model enables multi-task deep learning leveraging the data from multiple domains. The joint multi-domain recurrent neural (JRNN) can leverage semantic intents (such as, finding or identifying, e.g., a domain specific goal) and slots (such as, dates, times, locations, subjects, etc.) across multiple domains.