Methods and apparatus for deep interaction analysis
AssigneeNice Systems Ltd.
InventorsYuval Lubowich, Oren Pereg, Ezra Daya
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Abstract
A method and apparatus for automatically sectioning an interaction into sections, in order to get more insight into interactions. The method and apparatus include training, in which a model is generated upon training interactions and available tagging information, and run-time in which the model is used towards sectioning further interactions. The method and apparatus operate on context units within the interaction, wherein each context unit is characterized by a feature vector relate to textual, acoustic or other characteristics of the context unit.
Claims20
A method for automatically sectioning an audio signal of an interaction held in a call center, into sections representing the flow of the interaction, the method comprising the steps of:
- receiving the audio signal from a logging and capturing unit associated with the call center;
- performing audio analysis on the audio signal for obtaining run-time data;
- segmenting the audio signal into at least one context unit;
- extracting a feature vector comprising at least one run-time feature of the at least one context unit, using the run-time data;
- classifying the at least one context unit using a sectioning model and the feature vector, to obtain at least one section label to be associated with the at least one context unit;
- and
- grouping context units assigned identical labels into one section.
An apparatus for automatically sectioning an interaction held in a call center, into sections representing the flow of the interaction, based on at least one training interaction, the apparatus comprising:
- an interaction receiving component arranged to receive at least one first audio signal representing the interaction or at least one second audio signal representing the training interaction;
- an extraction component arranged to extract data from the at least one first audio signal or the at least one second audio signal;
- a context unit segmentation component arranged to segment the at least one first audio signal or the at least one second audio signal into context units;
- a feature vector determination component arranged to generate a feature vector comprising at least one feature based on the data extracted from the at least one first audio signal or the at least one second audio signal;
- and
- a sectioning component arranged to apply a sectioning model on the feature vector.
A computer readable storage medium containing a set of instructions for a general purpose computer, the set of instructions comprising:
- receiving an audio signal representing an interaction captured within a call center;
- performing audio analysis on the audio signal for obtaining tested data;
- segmenting the audio signal into at least one tested context unit;
- extracting a tested feature vector comprising at least one feature of the at least one context unit, using the data;
- classifying the at least one context unit using a sectioning model and the tested feature vector, to obtain at least one section label to be associated with the at least one context unit;
- and
- grouping context units assigned identical labels into one section.
Dependencies are inferred from the claim text.