公开(公告)号：US12236204B2

公开(公告)日：2025-02-25

申请号：US18074394

申请日：2022-12-02

Applicant: NVIDIA CORPORATION

Inventor： Shubhadeep Das ,  Yi-Hui Lee ,  Oluwatobi Olabiyi ,  Zhilin Wang

IPC: G06F40/56 ,  G06F40/284

Abstract: In various examples, a technique for slot filling includes receiving a natural language sentence from a user and identifying a first mention span included in the natural language sentence. The technique also includes determining, using a first machine learning model, that the first mention span is associated with a first slot class included in a set of slot classes based on a set of slot class descriptions corresponding to the set of slot classes.

公开(公告)号：US20240370690A1

公开(公告)日：2024-11-07

申请号：US18309890

申请日：2023-05-01

Applicant: NVIDIA Corporation

Inventor： Sagar Bogadi Manjunath ,  Shubhadeep Das ,  Sumit Kumar Bhattacharya ,  Oluwatobi Olabiyi

IPC: G06N3/006 ,  G06N3/045

Abstract: In various examples, query response generation using entity linking for conversational AI systems and applications is described herein. Systems and methods are disclosed that generate embeddings associated with entities that a dialogue system is trained to interpret. The systems and methods may then use the embeddings to interpret requests. For instance, when receiving a request, the systems and methods may generate at least an embedding for an entity included in the request and compare the embedding to the stored embeddings in order to determine that the entity from the request is related to one of the stored entities. The systems and methods may then use this relationship to generate the response to the query. This way, even if the entity is not an exact match to a stored entity, the systems and methods are still able to interpret the query from the user.

公开(公告)号：US20240363104A1

公开(公告)日：2024-10-31

申请号：US18766466

申请日：2024-07-08

Applicant: NVIDIA Corporation

Inventor： Shubhadeep Das ,  Sumit Bhattacharya ,  Ratin Kumar

IPC: G10L15/18 ,  G10L13/02 ,  G10L15/22 ,  G10L15/30

CPC classification number: G10L15/1815 ,  G10L13/02 ,  G10L15/22 ,  G10L15/30

Abstract: In various examples, systems and methods of the present disclosure combine open and closed dialog systems into an intelligent dialog management system. A text query may be processed by a natural language understanding model trained to associate the text query with a domain tag, intent classification, and/or input slots. Using the domain tag, the natural language understanding model may identify information in the text query corresponding to input slots needed for answering the text query. The text query and related information may then be passed to a dialog manager to direct the text query to the proper domain dialog system. Responses retrieved from the domain dialog system may be provided to the user via text output and/or via a text to speech component of the dialog management system.

公开(公告)号：US20240176808A1

公开(公告)日：2024-05-30

申请号：US18172571

申请日：2023-02-22

Applicant: NVIDIA Corporation

Inventor： Shubhadeep Das ,  Sumit Kumar Bhattacharya ,  Oluwatobi Olabiyi

IPC: G06F16/33 ,  G06F16/338

CPC classification number: G06F16/3344 ,  G06F16/338

Abstract: In various examples, contextual data may be generated using structured and unstructured data for conversational AI systems and applications. Systems and methods are disclosed that use structured data (converted to unstructured form) and unstructured data, such as from a knowledge database(s), to generate contextual data. For instance, the contextual data may represent text (e.g., narratives), where a first portion of the text is generated using the structured data and a second portion of the text is generated using the unstructured data. The systems and methods may then use a neural network(s), such as a neural network(s) associated with a dialogue manager, to process input data representing a request (e.g., a query) and the contextual data in order to generate a response to the request. For instance, if the request includes a query for information associated with a topic, the neural network(s) may generate a response that includes the requested information.

公开(公告)号：US11769495B2

公开(公告)日：2023-09-26

申请号：US18067217

申请日：2022-12-16

Applicant: NVIDIA Corporation

Inventor： Shubhadeep Das ,  Sumit Bhattacharya ,  Ratin Kumar

IPC: G10L15/22 ,  G10L15/18 ,  G10L13/02 ,  G10L15/30

CPC classification number: G10L15/1815 ,  G10L13/02 ,  G10L15/22 ,  G10L15/30

Abstract: In various examples, systems and methods of the present disclosure combine open and closed dialog systems into an intelligent dialog management system. A text query may be processed by a natural language understanding model trained to associate the text query with a domain tag, intent classification, and/or input slots. Using the domain tag, the natural language understanding model may identify information in the text query corresponding to input slots needed for answering the text query. The text query and related information may then be passed to a dialog manager to direct the text query to the proper domain dialog system. Responses retrieved from the domain dialog system may be provided to the user via text output and/or via a text to speech component of the dialog management system.

公开(公告)号：US20230064049A1

公开(公告)日：2023-03-02

申请号：US17462833

申请日：2021-08-31

Applicant: Nvidia Corporation

Inventor： Sakthivel Sivaraman ,  Nishant Puri ,  Yuzhuo Ren ,  Atousa Torabi ,  Shubhadeep Das ,  Niranjan Avadhanam ,  Sumit Kumar Bhattacharya ,  Jason Roche

IPC: G06K9/00 ,  G06T7/73 ,  G06F3/01 ,  G06F16/632 ,  G06T15/06

Abstract: Interactions with virtual systems may be difficult when users inadvertently fail to provide sufficient information to proceed with their requests. Certain types of inputs, such as auditory inputs, may lack sufficient information to properly provide a response to the user. Additional information, such as image data, may enable user gestures or poses to supplement the auditory inputs to enable response generation without requesting additional information from users.