Escalation detection using sentiment analysis
US-10224059-B2 · Mar 5, 2019 · US
US10573337B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10573337-B2 |
| Application number | US-201816202155-A |
| Country | US |
| Kind code | B2 |
| Filing date | Nov 28, 2018 |
| Priority date | Jul 21, 2016 |
| Publication date | Feb 25, 2020 |
| Grant date | Feb 25, 2020 |
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Systems and methods for computer-based escalation detection are disclosed. In embodiments, a method includes: determining an occurrence of an interaction event between a first party and a second party within a recording including audio data; analyzing the audio data; determining, based on the analyzing the audio data, an escalation during the interaction event to generate escalation data; saving the escalation data; partitioning each interaction event into a plurality of sections, wherein a first section represents a start of the interaction event, and another section represents an end of the interaction event; assigning a sentiment score for each of the plurality of sections; and calculating an overall sentiment score for the interaction event by combining the sentiment scores for each of the plurality of sections, wherein the saved escalation data includes the overall sentiment score.
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What is claimed is: 1. A computer-implemented method, comprising: determining, by a computer device, an occurrence of an interaction event between a first person of interest and one or more members of the public within an audio-video recording including audio data, wherein the determining the occurrence of the first interaction event includes detecting that the first person of interest or the one or more members of the public has entered a frame of the audio-video recording for a predetermined time period; analyzing, by the computer device, the audio data; determining, by the computer device and based on the analyzing the audio data, an escalation during the interaction event to generate escalation data; saving, by the computer device, the escalation data partitioning, by the computer device, each interaction event into a plurality of sections, wherein a first section represents a start of the interaction event, and another section represents an end of the interaction event; assigning, by the computer device, a sentiment score for each of the plurality of sections; and calculating, by the computer device, an overall sentiment score for the interaction event by combining the sentiment scores for each of the plurality of sections, wherein the saved escalation data includes the overall sentiment score. 2. The computer-implemented method of claim 1 , wherein the determining the occurrence of an interaction event further includes detecting, by the computing device, a threshold level of sound in the audio data. 3. The computer-implemented method of claim 1 , further comprising comparing, by the computing device, the escalation data to historic escalation data. 4. The computer-implemented method of claim 1 , further comprising: gathering, by the computing device, overall sentiment scores for a plurality of interaction events involving the first person of interest; and monitoring, by the computing device, the overall sentiment scores over time to determine any increase or decrease in the overall sentiment scores. 5. The computer-implemented method of claim 4 , further comprising sending, by the computing device, data analytics results to a client server, wherein the data analytics results indicate that the overall sentiment scores increased over time. 6. The computer-implemented method of claim 1 , further comprising: converting, by the computing device, the audio data into text, wherein the analyzing the audio data comprises analyzing the text for a change in tone over time. 7. The computer-implemented method of claim 6 , wherein the audio data as a whole is converted to text and analyzed without distinguishing between audio data generated by the first person of interest and audio data generated by the one or more members of the public. 8. A computer program product for detecting escalation the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computing device to cause the computing device to: determine an occurrence of an interaction event between a first person of interest and one or more members of the public within an audio-video recording including audio data, wherein the determining the occurrence of the first interaction event includes detecting that the first person of interest or the one or more members of the public has entered a frame of the audio-video recording for a predetermined time period; analyze the audio data for a change in tone over time; analyze the audio data for a presence of any negative tones; determine whether the change in tone, the presence of any negative tones, or a combination of the change in tone and the presence of any negative tones, indicates an escalation during the interaction event to generate escalation data; save the escalation data; compare the saved escalation data to historic escalation data; gather overall sentiment scores for a plurality of interaction events involving the first person of interest; and monitor the overall sentiment scores over time to determine any increase or decrease in the overall sentiment scores. 9. The computer program product of claim 8 , wherein the program instructions to determine the occurrence of an interaction event include instructions to detect a threshold level of sound in the audio data. 10. The computer program product of claim 8 , wherein the program instructions further cause the computing device to send data analytics results to a client server, wherein the data analytics results indicate that the overall sentiment scores increased over time. 11. The computer program product of claim 8 , the program instructions further causing the computing device to: partition each interaction event into a plurality of sections, wherein a first section represents a start of the interaction event, and another section represents an end of the interaction event; assign a sentiment score for each of the plurality of sections based on the changes in the tone over time and the presence of any negative tones; and calculate an overall sentiment score for the interaction event by combining the sentiment scores for each of the plurality of sections, wherein the saved escalation data includes the overall sentiment score. 12. The computer program product of claim 8 , the program instructions further causing the computing device to convert the audio data into text, wherein the instructions to analyze the audio data for a change in tone over time and the instructions to analyze the audio data for the presence of any negative tones comprises analyzing the text. 13. The computer program product of claim 12 , wherein the audio data as a whole is converted to text and analyzed without distinguishing between audio data generated by the first person of interest and audio data generated by the one or more members of the public. 14. A system for detecting escalation, comprising: a CPU, a computer readable memory and a computer readable storage medium associated with a computing device; program instructions to determine an occurrence of a first interaction event between a first person of interest and one or more members of the public within an audio-video recording including audio data and video data, wherein the determining the occurrence of the first interaction event includes detecting that the first person of interest or the one or more members of the public has entered a frame of the audio-video recording for a predetermined time period; program instructions to analyze the audio data for a change in tone over time; program instructions to analyze the audio data for a presence of any negative tones; program instructions to determine whether the change in tone, the presence of any negative tones, or a combination of the change in tone and the presence of any negative tones, indicates an escalation during the first interaction event to generate escalation data; program instructions to save the escalation data; program instructions to gather overall sentiment scores for a plurality of interaction events involving the first person of interest; and program instructions to monitor the overall sentiment scores over time to determine any increase or decrease in the overall sentiment scores, wherein the program instructions are stored on the computer readable storage medium for execution by the CPU via the computer readable memory. 15. The system of claim 14 , further comprising: program instructions to graph the overall sentiment scores, wherein the monitoring comprises detecting a pattern of increasing overall sentiment scores over tim
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