Automated support center call topic identification

A computing system comprising:

• one or more computing devices operable to:
• generate, based on a first plurality of digitized voice signal recordings, a plurality of first datasets that correspond to ones of the first plurality of digitized voice signal recordings, each digitized voice signal recording in the first plurality of digitized voice signal recordings corresponding to a support call of a first plurality of support calls between a technician and a support representative providing support to the technician, each first dataset comprising one or more textual documents that comprise words spoken during the corresponding support call between the technician and the support representative;
• train, using the plurality of first datasets, an unsupervised learning model operative to identify clusters of first datasets from the plurality of first datasets based on similarity to a corresponding topic of a plurality of first topics, each first topic of the plurality of first topics comprising a first set of topic terms;
• obtain, from the unsupervised learning model, the plurality of first topics, each first topic of the plurality of first topics comprising information indicative of a corresponding first set of topic terms and a respective cluster of first datasets;
• assign, to a respective first topic of the plurality of first topics, a textual description based on the corresponding first set of topic terms, wherein the textual description comprises a category and a subcategory of a plurality of subcategories corresponding to the category, wherein the category and the subcategory are descriptive of the respective first topic and the respective cluster of first datasets;
• and
• output information that corresponds to at least one first topic of the plurality of first topics.

A non-transitory computer-readable storage medium that includes executable instructions operable to cause one or more computing devices to:

• generate, based on a first plurality of digitized voice signal recordings, a plurality of first datasets that correspond to ones of the first plurality of digitized voice signal recordings, each digitized voice signal recording in the first plurality of digitized voice signal recordings corresponding to a support call of a first plurality of support calls between a technician and a support representative providing support to the technician, each first dataset comprising one or more textual documents that comprise words spoken during the corresponding support call between the technician and the support representative;
• train, using the plurality of first datasets, an unsupervised learning model operative to identify clusters of first datasets from the plurality of first datasets based on similarity to a corresponding topic of a plurality of first topics, each first topic of the plurality of first topics comprising a first set of topic terms;
• obtain, from the unsupervised learning model, the plurality of first topics, each first topic of the plurality of first topics comprising information indicative of a corresponding first set of topic terms and a respective cluster of first datasets;
• assign, to a respective first topic of the plurality of first topics, a textual description based on the corresponding first set of topic terms, wherein the textual description comprises a category and a subcategory of a plurality of subcategories corresponding to the category, wherein the category and the subcategory are descriptive of the respective first topic and the respective cluster of first datasets;
• and
• output information that corresponds to at least one first topic of the plurality of first topics.