1. A computerized 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 at least a part of the audio signal from a logging and capturing unit comprising a computing platform and associated with the call center, the at least a part of the audio signal comprises a non-training production run-time interaction; performing audio analysis on the at least a part of the audio signal for obtaining run-time data; segmenting the at least a part of the audio signal into at least one context unit; extracting a feature vector as a multi-valued construct 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 subsequently grouping context units assigned identical labels into one section, wherein the method is carried out by an at least one processing apparatus.
1. A computerized 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 at least a part of the audio signal from a logging and capturing unit comprising a computing platform and associated with the call center, the at least a part of the audio signal comprises a non-training production run-time interaction; performing audio analysis on the at least a part of the audio signal for obtaining run-time data; segmenting the at least a part of the audio signal into at least one context unit; extracting a feature vector as a multi-valued construct 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 subsequently grouping context units assigned identical labels into one section, wherein the method is carried out by an at least one processing apparatus. 13. The method of claim 1 further comprising a step of comparing sectioning statistics between at least two categories or between at least two agents, or a step of using the at least one section label as a categorization criteria.