The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 05, 2025

Filed:

Nov. 03, 2021
Applicant:

Servicenow, Inc., Santa Clara, CA (US);

Inventors:

Edwin Sapugay, Foster City, CA (US);

Anil Kumar Madamala, Sunnyvale, CA (US);

Maxim Naboka, Santa Clara, CA (US);

Srinivas Satyasai Sunkara, Sunnyvale, CA (US);

Lewis Savio Landry Santos, Santa Clara, CA (US);

Murali B. Subbarao, Saratoga, CA (US);

Assignee:

ServiceNow, Inc., Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/30 (2020.01); G06F 40/205 (2020.01); G06F 40/211 (2020.01); G06N 5/022 (2023.01); G06N 20/00 (2019.01); G10L 15/19 (2013.01); G10L 15/22 (2006.01); G10L 15/16 (2006.01); G10L 15/18 (2013.01);
U.S. Cl.
CPC ...
G06F 40/30 (2020.01); G06F 40/205 (2020.01); G06F 40/211 (2020.01); G06N 5/022 (2013.01); G06N 20/00 (2019.01); G10L 15/19 (2013.01); G10L 15/22 (2013.01); G10L 15/16 (2013.01); G10L 15/1807 (2013.01); G10L 15/1822 (2013.01); G10L 2015/223 (2013.01); G10L 2015/225 (2013.01);
Abstract

Present embodiment include a prosody subsystem of a natural language understanding (NLU) framework that is designed to analyze collections of written messages for various prosodic cues to break down the collection into a suitable level of granularity (e.g., into episodes, sessions, segments, utterances, and/or intent segments) for consumption by other components of the NLU framework, enabling operation of the NLU framework. These prosodic cues may include, for example, source prosodic cues that are based on the author and the conversation channel associated with each message, temporal prosodic cues that are based on a respective time associated with each message, and/or written prosodic cues that are based on the content of each message. For example, to improve the domain specificity of the agent automation system, intent segments extracted by the prosody subsystem may be consumed by a training process for a ML-based structure subsystem of the NLU framework.


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