Abstract:
A method and apparatus for automated categorization of an interaction between a member of an organization and a second party. The method comprises defining one or more criteria and one or more categories, wherein each category relates to a combination of one or more criteria. The criteria involve data extracted from the interactions as well as external data. Each interaction is checked against the criteria, and is then assigned to one or more categories according to the met criteria. An optional evaluation of the categorization step, and improvement of the categorization if the evaluation results fall below a threshold are disclosed.
Abstract:
An apparatus and method for the analysis, marking and summing of audio channel content and control data, the apparatus and method generating a summed signal carrying combined audio content, marking and summing data in the summed signal.
Abstract:
An apparatus and method for the analysis, marking and summing of audio channel content and control data, the apparatus and method generating a summed signal carrying combined audio content, marking and summing data in the summed signal.
Abstract:
A method and apparatus (100) for capturing and analyzing customer interactions, the apparatus comprising a multi-segment interaction capture device (324), an initial set up and calibration device (326), a pre-processing and context extraction device (328) and a rule-based analysis engine (300).
Abstract:
An apparatus and method for detecting a fraud or fraud attempt in a captured interaction. The method comprising a selection step in which interactions suspected as capturing fraud attempts are selected for further analysis, and assigned a first fraud probability, and a fraud detection step in which the voice is scored against one or more voice prints, of the same alleged customer or of known fraudsters. The first fraud or fraud attempt probability is combined with the result of the scoring of the fraud detection step, to generate a total fraud or fraud attempt probability. If the total fraud or fraud attempt probability exceeds a threshold, a notification is issued. The selection, scoring and combination thereof are performed using user-defined rules and thresholds.
Abstract:
A method and apparatus for spotting a target speaker within a call interaction by generating speaker models based on one or more speaker's speech; and by searching for speaker models associated with one or more target speaker speech files.
Abstract:
A method and apparatus for spotting a target speaker within a call interaction by generating speaker models (98) based on one or more speaker's speech; and by searching for speaker models (110) associated with one or more target speaker speech files.
Abstract:
A method and apparatus for automated categorization of an interaction between a member of an organization and a second party. The method comprises defining one or more criteria and one or more categories, wherein each category relates to a combination of one or more criteria. The criteria involve data extracted from the interactions as well as external data. Each interaction is checked against the criteria, and is then assigned to one or more categories according to the met criteria. An optional evaluation of the categorization step, and improvement of the categorization if the evaluation results fall below a threshold are disclosed.
Abstract:
A method and apparatus for segmenting an audio interaction, by locating anchor segment fro each side of the interaction, iteratively classifying additional segments into one of the two sides, and scoring the resulting segmentation, If the score result is below a threshold, the process is repeated until the segmentation score is satisfactory or until a stopping criterion is met. The anchoring and the scoring steps comprise using additional data associated with the interaction, a speaker thereof, internal or external information related to the interaction or to a speaker thereof or the like.
Abstract:
A method and apparatus for segmenting an audio interaction, by locating anchor segment fro each side of the interaction, iteratively classifying additional segments into one of the two sides, and scoring the resulting segmentation, If the score result is below a threshold, the process is repeated until the segmentation score is satisfactory or until a stopping criterion is met. The anchoring and the scoring steps comprise using additional data associated with the interaction, a speaker thereof, internal or external information related to the interaction or to a speaker thereof or the like.