Invention Grant
- Patent Title: Distributed machine-learned emphatic communication for machine-to-human and machine-to-machine interactions
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Application No.: US16192327Application Date: 2018-11-15
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Publication No.: US11037576B2Publication Date: 2021-06-15
- Inventor: Aaron K. Baughman , Mauro Marzorati , Gary Francis Diamanti , Sarbajit K. Rakshit
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Garg Law Firm, PLLC
- Agent Rakesh Garg; James Nock
- Main IPC: G10L17/26
- IPC: G10L17/26 ; G10L15/30 ; G10L15/18 ; G06N20/00 ; G10L17/04 ; G10L17/22 ; H04L12/58 ; H04M3/493 ; H04M3/22 ; G10L15/26 ; G10L17/00 ; G10L15/22
Abstract:
A system determines if a call participant of a call between the call participant and a voice response system is a human or a machine. Responsive to determining that the call participant is a human, an emotional state of the call participant is determined. Environmental information of an environment associated with the call participant is receiving. A receptiveness level of the call participant is determined based upon the emotional state and the environmental information. A message to the call participant is determined based upon the receptiveness level and one or more machine-learning models.
Public/Granted literature
Information query
