Method and system for confidential sentiment analysis

Abstract

A method for anonymizing data includes receiving call data of a call in an interaction recording system located behind a firewall of an internal network sub-environment, and within the internal network sub-environment: (i) storing the call data including interaction metadata, (ii) generating a speech-to-text transcript corresponding to words spoken by one or more callers, and (iii) generating an anonymized transcript by anonymizing personally identifiable information. A computing system includes a processor, and a memory including computer executable instructions that, when executed by the one processor, cause the system to perform the method. A non-transitory computer readable medium contains program instructions that when executed, cause a computer system to perform the method.

What is claimed: 
     
         1 . A computer implemented method for anonymizing data, comprising:
 receiving call data of a call in an interaction recording system of a call center recorder, wherein the interaction recording system is located behind a firewall of an internal network sub-environment; and   within the internal network sub-environment:
 (i) storing the call data in an electronic database, wherein the call data includes interaction metadata, 
 (ii) generating a speech-to-text transcript by analyzing call audio in the call data, wherein the speech-to-text transcript corresponds to words spoken by one or more callers during the call, and 
 (iii) generating an anonymized transcript corresponding to the speech-to-text transcript by identifying, removing, replacing, or obscuring one or more alpha-numeric personally identifiable information. 
   
     
     
         2 . The method of  claim 1 , wherein the interaction recording system is located behind the firewall of the internal network sub-environment, the method further comprising:
 collecting a consent of the caller to store the call data.   
     
     
         3 . The method of  claim 1 , wherein storing the call data includes storing caller identification information. 
     
     
         4 . The method of  claim 1 , wherein generating the anonymized transcript by identifying, removing, replacing, or obscuring one or more alpha-numeric personally identifiable information is based on matching regular expression patterns against the speech-to-text transcript. 
     
     
         5 . The method of  claim 1 , wherein generating the anonymized transcript by identifying, removing, replacing, or obscuring one or more alpha-numeric personally identifiable information is based on matching keywords in the speech-to-text transcript to one or more corpora of words. 
     
     
         6 . The method of  claim 1 , wherein generating the anonymized transcript by identifying, removing, replacing, or obscuring one or more alpha-numeric personally identifiable information is based on analyzing the speech-to-text transcript using a trained machine learning model. 
     
     
         7 . The method of  claim 1 , further comprising:
 generating a sentiment score by analyzing the anonymized transcript using a sentiment analysis service.   
     
     
         8 . The method of  claim 7 , wherein generating the sentiment score by analyzing the anonymized transcript using the sentiment analysis service includes generating a time series wherein each time step corresponds to a time in the anonymized transcript, and each time step is associated with a sentiment score, wherein the sentiment score indicates the sentiment at the respective time step. 
     
     
         9 . The method of  claim 7 , wherein generating the sentiment score by analyzing the anonymized transcript using the sentiment analysis service includes generating an intra-call sentiment score. 
     
     
         10 . A computing system for anonymizing data, comprising
 one or more processors, and   a memory including computer executable instructions that, when executed by the one or more processors, cause the computing system to:
 receive call data of a call in an interaction recording system of a call center recorder, wherein the interaction recording system is located behind a firewall of an internal network sub-environment; and 
 within the internal network sub-environment:
 (i) store the call data in an electronic database, wherein the call data includes interaction metadata, 
 (ii) generate a speech-to-text transcript by analyzing call audio in the call data, wherein the speech-to-text transcript corresponds to words spoken by one or more callers during the call, and 
 (iii) generate an anonymized transcript corresponding to the speech-to-text transcript by identifying, removing, replacing, or obscuring one or more alpha-numeric personally identifiable information. 
 
   
     
     
         11 . The computing system of  claim 10 , the memory containing further instructions that, when executed by the one or more processors, cause the computing system to:
 collect a consent of the caller to store the call data.   
     
     
         12 . The computing system of  claim 10 , the memory containing further instructions that, when executed by the one or more processors, cause the computing system to:
 generate the anonymized transcript by matching regular expression patterns against the speech-to-text transcript.   
     
     
         13 . The computing system of  claim 10 , the memory containing further instructions that, when executed by the one or more processors, cause the computing system to:
 generate the anonymized transcript by matching keywords in the speech-to-text transcript to one or more corpora of words.   
     
     
         14 . The computing system of  claim 10 , the memory containing further instructions that, when executed by the one or more processors, cause the computing system to:
 generate the anonymized transcript by analyzing the speech-to-text transcript using a trained machine learning model.   
     
     
         15 . The computing system of  claim 10 , the memory containing further instructions that, when executed by the one or more processors, cause the computing system to:
 generate a time series wherein each time step corresponds to a time in the anonymized transcript, and each time step is associated with a sentiment score, wherein the sentiment score indicates a sentiment at the respective time step.   
     
     
         16 . The computing system of  claim 10 , the memory containing further instructions that, when executed by the one or more processors, cause the computing system to:
 generating an intra-call sentiment score.   
     
     
         17 . A non-transitory computer readable medium containing program instructions for anonymizing data that when executed, cause a computer system to:
 receive call data of a call in an interaction recording system of a call center recorder, wherein the interaction recording system is located behind a firewall of an internal network sub-environment; and   within the internal network sub-environment:
 (i) store the call data in an electronic database, wherein the call data includes interaction metadata, 
 (ii) generate a speech-to-text transcript by analyzing call audio in the call data, wherein the speech-to-text transcript corresponds to words spoken by one or more callers during the call, and 
 (iii) generate an anonymized transcript corresponding to the speech-to-text transcript by identifying, removing, replacing, or obscuring one or more alpha-numeric personally identifiable information. 
   
     
     
         18 . The non-transitory computer readable medium of  claim 17 , including further program instructions that when executed, cause a computer system to:
 generate the anonymized transcript by matching regular expression patterns against the speech-to-text transcript.   
     
     
         19 . The non-transitory computer readable medium of  claim 17 , including further program instructions that when executed, cause a computer system to:
 generate the anonymized transcript by matching keywords in the speech-to-text transcript to one or more corpora of words.   
     
     
         20 . The non-transitory computer readable medium of  claim 17 , including further program instructions that when executed, cause a computer system to:
 generate the anonymized transcript by analyzing the speech-to-text transcript using a trained machine learning model.