Generating featureless service provider matches

Abstract

The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize featureless supervised or unsupervised machine learning to generate service provider match predictions based on raw communication data. In one or more embodiments, the disclosed systems utilize a trained service provider match neural network to generate a service provider match prediction based on raw communication data associated with an incoming audio, text, or video communication. In response to the generated service provider match prediction, the disclosed systems can route the incoming communication to the matched service provider.

We claim: 
     
         1 . A method comprising:
 identifying match prediction training data, wherein the match prediction training data comprises a plurality of instances of raw communication match data and a plurality of service provider match markers, and further wherein each instance of raw communication match data of the plurality of instances of raw communication match data corresponds to a service provider match marker of the plurality of service provider match markers; and   training a service provider neural network using the match prediction training data by, for each instance of raw communication data:
 passing the instance of raw communication data to the service provider match neural network; 
 receiving a prediction from the service provider match neural network for the instance of raw communication data; 
 comparing the prediction to the service provider match marker corresponding to the instance of raw communication match data; and 
   modifying one or more parameters of one or more layers of the service provider match neural network based on the comparing.   
     
     
         2 . The method of  claim 1 , wherein passing the instance of raw communication data to the service provider match neural network comprises:
 generating an input vector from the instance of raw communication data; and   passing the generated input vector to the service provider match neural network.   
     
     
         3 . The method of  claim 1 , wherein each instance of raw communication data comprises recorded audio, and each corresponding service provider match marker comprises one or more of a service provider identifier or a plurality of attributes of a predicted service provider. 
     
     
         4 . The method of  claim 1 , wherein the prediction for the instance of raw communication data comprises a first plurality of attributes and the service provider match marker corresponding to the instance of raw communication data comprises a second plurality of attributes, and comparing the prediction to the service provider match marker corresponding to the instance of raw communication match data comprises:
 determining that more than a threshold number of attributes from the first plurality of attributes match attributes from the second plurality of attributes; and   in response to the determination, determining that the prediction for the instance of raw communication data matches the service provider match marker corresponding to the instance of raw communication data.   
     
     
         5 . The method of  claim 1 , further comprising:
 receiving a communication from a client device associated with a contacting user;   extracting raw communication data associated with the contacting user from the received communication;   providing the extracted raw communication data to the service provider match neural network;   receiving a first service provider match prediction from the service provider match neural network based on the provided extracted raw communication data; and   providing the first service provider match prediction to a customer request system.   
     
     
         6 . The method of  claim 5 , further comprising:
 receiving, from the customer request system, an indication that the first service provider match prediction cannot be accommodated;   in response to receiving the indication, modifying one or more parameters of one or more layers of the service provider match neural network;   providing the extracted raw communication data to the service provider match neural network; and   receiving a second service provider match prediction from the service provider match neural network based on the extracted raw communication data.   
     
     
         7 . The method of  claim 5 , wherein providing the extracted raw communication data to the service provider match neural network comprises:
 generating an input vector based on the raw communication data; and   providing the generated input vector to the service provider match neural network.   
     
     
         8 . A system comprising:
 at least one processor; and   at least one non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the system to:
 identify match prediction training data, wherein the match prediction training data comprises a plurality of instances of raw communication match data and a plurality of service provider match markers, and further wherein each instance of raw communication match data of the plurality of instances of raw communication match data corresponds to a service provider match marker of the plurality of service provider match markers; and 
 train a service provider neural network using the match prediction training data by, for each instance of raw communication data:
 passing the instance of raw communication data to the service provider match neural network; 
 receiving a prediction from the service provider match neural network for the instance of raw communication data; 
 comparing the prediction to the service provider match marker corresponding to the instance of raw communication match data; and 
 modifying one or more parameters of one or more layers of the service provider match neural network based on the comparing. 
 
   
     
     
         9 . The system of  claim 8 , wherein passing the instance of raw communication data to the service provider match neural network comprises:
 generating an input vector from the instance of raw communication data; and   passing the generated input vector to the service provider match neural network.   
     
     
         10 . The system of  claim 8 , wherein each instance of raw communication data comprises recorded audio, and each corresponding service provider match marker comprises one or more of a service provider identifier or a plurality of attributes of a predicted service provider. 
     
     
         11 . The system of  claim 8 , wherein the prediction for the instance of raw communication data comprises a first plurality of attributes and the service provider match marker corresponding to the instance of raw communication data comprises a second plurality of attributes, and comparing the prediction to the service provider match marker corresponding to the instance of raw communication match data comprises:
 determining that more than a threshold number of attributes from the first plurality of attributes match attributes from the second plurality of attributes; and   in response to the determination, determining that the prediction for the instance of raw communication data matches the service provider match marker corresponding to the instance of raw communication data.   
     
     
         12 . The system of  claim 8 , further storing instructions thereon that, when executed by the at least one processor, cause the system to:
 receive a communication from a client device associated with a contacting user;   extract raw communication data associated with the contacting user from the received communication;   provide the extracted raw communication data to the service provider match neural network;   receive a first service provider match prediction from the service provider match neural network based on the provided extracted raw communication data; and   provide the first service provider match prediction to a customer request system.   
     
     
         13 . The system of  claim 12 , further storing instructions thereon that, when executed by the at least one processor, cause the system to:
 receive, from the customer request system, an indication that the first service provider match prediction cannot be accommodated;   in response to receiving the indication, modify one or more parameters of one or more layers of the service provider match neural network;   provide the extracted raw communication data to the service provider match neural network; and   receive a second service provider match prediction from the service provider match neural network based on the extracted raw communication data.   
     
     
         14 . The system of  claim 13 , wherein providing the extracted raw communication data to the service provider match neural network comprises:
 generating an input vector based on the raw communication data; and   providing the generated input vector to the service provider match neural network.   
     
     
         15 . A non-transitory computer-readable medium storing instructions thereon that, when executed by at least one processor, cause a computer system to:
 identify match prediction training data, wherein the match prediction training data comprises a plurality of instances of raw communication match data and a plurality of service provider match markers, and further wherein each instance of raw communication match data of the plurality of instances of raw communication match data corresponds to a service provider match marker of the plurality of service provider match markers; and   train a service provider neural network using the match prediction training data by, for each instance of raw communication data:
 passing the instance of raw communication data to the service provider match neural network; 
 receiving a prediction from the service provider match neural network for the instance of raw communication data; 
 comparing the prediction to the service provider match marker corresponding to the instance of raw communication match data; and 
 modifying one or more parameters of one or more layers of the service provider match neural network based on the comparing. 
   
     
     
         16 . The computer-readable medium of  claim 15 , wherein passing the instance of raw communication data to the service provider match neural network comprises:
 generating an input vector from the instance of raw communication data; and   passing the generated input vector to the service provider match neural network.   
     
     
         17 . The computer-readable medium of  claim 15 , wherein each instance of raw communication data comprises recorded audio, and each corresponding service provider match marker comprises one or more of a service provider identifier or a plurality of attributes of a predicted service provider. 
     
     
         18 . The computer-readable medium of  claim 15 , wherein the prediction for the instance of raw communication data comprises a first plurality of attributes and the service provider match marker corresponding to the instance of raw communication data comprises a second plurality of attributes, and comparing the prediction to the service provider match marker corresponding to the instance of raw communication match data comprises:
 determining that more than a threshold number of attributes from the first plurality of attributes match attributes from the second plurality of attributes; and   in response to the determination, determining that the prediction for the instance of raw communication data matches the service provider match marker corresponding to the instance of raw communication data.   
     
     
         19 . The computer-readable medium of  claim 15 , further storing instructions thereon that, when executed by the at least one processor, cause the computer system to:
 receive a communication from a client device associated with a contacting user;   extract raw communication data associated with the contacting user from the received communication;   provide the extracted raw communication data to the service provider match neural network;   receive a first service provider match prediction from the service provider match neural network based on the provided extracted raw communication data; and   provide the first service provider match prediction to a customer request system.   
     
     
         20 . The computer-readable medium of  claim 19 , further storing instructions thereon that, when executed by the at least one processor, cause the computer system to:
 receive, from the customer request system, an indication that the first service provider match prediction cannot be accommodated;   in response to receiving the indication, modify one or more parameters of one or more layers of the service provider match neural network;   provide the extracted raw communication data to the service provider match neural network; and   receive a second service provider match prediction from the service provider match neural network based on the extracted raw communication data.