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13 条记录 (耗时 0.017 秒)

    Learning based metric determination for service sessions
    2.
    发明授权
    Learning based metric determination for service sessions 有权

    公开(公告)号：US11272057B1

    公开(公告)日：2022-03-08

    申请号：US17096544

    申请日：2020-11-12

    申请人： United Services Automobile Association (USAA)

    发明人： Eric J. Smith ,  John McChesney TenEyck, Jr. ,  Gregory Yarbrough ,  Vijay Jayapalan

    IPC分类号： H04M3/51 ,  H04M3/523

    摘要： Techniques are described for generating metrics about an individual's experience. One of the method describes providing, by at least one processor, the session record as input to at least one computer-processable model that determines, based on the session record, at least one metric for the service session, the at least one model having been trained, using machine learning and based at least partly on survey data for previous service sessions, to provide the at least one metric associated with the individual's experience. The method includes associating, by at least one processor, the metric of the individual's experience with the individual. The method also includes communicating, by at least one processor, the at least one metric for presentation through a user interface of a computing device.

    Rapid data access
    6.
    发明授权
    Rapid data access 有权

    公开(公告)号：US10771623B1

    公开(公告)日：2020-09-08

    申请号：US16583970

    申请日：2019-09-26

    申请人： United Services Automobile Association (USAA)

    发明人： Eric J. Smith ,  John McChesney TenEyck, Jr. ,  Gregory Yarbrough ,  Vijay Jayapalan

    IPC分类号： H04M3/42 ,  H04M3/51 ,  G06F9/455 ,  H04L9/06 ,  G06F16/182 ,  G06F9/451 ,  G06Q30/00

    摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coordinating callers with customer service representatives. One of the methods includes in response to receiving identification information from a caller, selecting a virtual machine from a plurality of virtual machines, the virtual machine configured to generate a virtual user interface for an application executing on the virtual machine. The method includes populating the virtual user interface with information about the caller based on the received identification information. The method includes sharing the virtual user interface with an application executing on a computer of a customer service representative. The method includes connecting the caller with the customer service representative.

    Learning based metric determination for service sessions
    9.
    发明授权
    Learning based metric determination for service sessions 有权

    公开(公告)号：US10440180B1

    公开(公告)日：2019-10-08

    申请号：US15616643

    申请日：2017-06-07

    申请人： United Services Automobile Association (USAA)

    发明人： Vijay Jayapalan ,  Gregory Yarbrough ,  Bipin Chadha ,  John McChesney TenEyck, Jr. ,  Eric J. Smith

    IPC分类号： H04M3/00 ,  H04M3/51 ,  G06N3/04 ,  G06N5/04 ,  G06Q30/00 ,  G06N20/00

    摘要： Techniques are described for generating metric(s) that predict survey score(s) for a service session. Model(s) may be trained, through supervised or unsupervised machine learning, using training data from previous service sessions between service representative(s) and individual(s). Training data may include, for previous service session(s), a session record (e.g., audio record) of the session and a set of survey scores provided by the serviced individual to rate the session on one or more criteria (e.g., survey questions). The model(s) may be trained to output, based on an input session record, metric(s) that each correspond to a survey score that would have been provided by the individual had they completed the survey. The model may be a concatenated model that is a combination of a language model output from a language classifier recurrent neural network, and an acoustic model output from an acoustic feature layer convolutional neural network.

    Learning based metric determination and clustering for service routing
    10.
    发明授权
    Learning based metric determination and clustering for service routing 有权

    公开(公告)号：US11140268B1

    公开(公告)日：2021-10-05

    申请号：US16895289

    申请日：2020-06-08

    申请人： United Services Automobile Association (USAA)

    发明人： Vijay Jayapalan ,  Gregory Yarbrough ,  Bipin Chadha ,  John McChesney TenEyck, Jr. ,  Eric J. Smith

    IPC分类号： H04M3/00 ,  H04M5/00 ,  H04L12/66 ,  H04M3/523 ,  G06N3/08

    摘要： Techniques are described for generating metric(s) that predict survey score(s) for a service session. Model(s) may be trained, through supervised or unsupervised machine learning, using training data such as communications from previous service sessions between service representative(s) and individual(s), and survey scores provided by the serviced individual to rate the session on one or more criteria (e.g., survey questions). The model(s) may be trained to output, based on an input session record, metric(s) that each correspond to a survey score that would have been provided by the individual had they completed the survey. The model may be a concatenated model that combines a language model output from a language classifier recurrent neural network, and an acoustic model output from an acoustic feature layer convolutional neural network. Individuals can be clustered according to the metric(s) and/or other factors, and the cluster(s) can be employed for routing incoming service requests.