Invention Grant
- Patent Title: Identification and classification of talk-over segments during voice communications using machine learning models
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Application No.: US17570121Application Date: 2022-01-06
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Publication No.: US11978442B2Publication Date: 2024-05-07
- Inventor: Gennadi Lembersky , Neta Rosenfeld
- Applicant: NICE LTD
- Applicant Address: IL Ra'anana
- Assignee: NICE LTD.
- Current Assignee: NICE LTD.
- Current Assignee Address: IL Ra'anana
- Agency: Haynes and Boone, LLP
- Main IPC: G10L15/00
- IPC: G10L15/00 ; G10L15/02 ; G10L15/04 ; G10L15/20 ; G10L15/22 ; G10L25/78 ; H04M3/51

Abstract:
A system and methods are provided to analyze audio signals from an incoming voice call. The system includes a processor and a computer readable medium operably coupled thereto, to perform voice analysis operations which include receiving a first audio signal comprising a first audio waveform of a first speech between at least two users during the incoming voice call, accessing speech segment parameters for analyzing the audio signals, determining one or more talk-over segments in the first audio waveform using the speech segment parameters, extracting audio features from each of the one or more talk-over segments, determining, using a machine learning (ML) model trained for interruption analysis of the audio signals, whether each of the one or more talk-over segments are a negative interruption or a non-negative interruption based on the audio features, and determining whether to output a first notification for the negative interruption or the non-negative interruption.
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