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Oren Pereg

Researcher at NICE Systems

Publications -  35
Citations -  1717

Oren Pereg is an academic researcher from NICE Systems. The author has contributed to research in topics: Audio analyzer & Computer science. The author has an hindex of 20, co-authored 31 publications receiving 1674 citations.

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Patent

Method, apparatus and system for capturing and analyzing interaction based content

TL;DR: In this article, a method and apparatus for capturing and analyzing customer interactions is described, 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).
Patent

Method and apparatus for fraud detection

TL;DR: In this paper, an apparatus and method for detecting a fraud or fraud attempt in a captured interaction is presented. But 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 is scored against one or more voice prints, of the same alleged customer or of known fraudsters.
Patent

Methods and apparatus for deep interaction analysis

TL;DR: In this article, a method and apparatus for automatically sectioning an interaction into sections, in order to get more insight into interactions, is presented, where a model is generated upon training interactions and available tagging information, and run-time in which the model is used towards sectioning further interactions.
PatentDOI

Method and apparatus for detection of sentiment in automated transcriptions

TL;DR: In this paper, a method for automatically detecting sentiments in an audio signal of an interaction held in a call center, including, receiving the audio signal from a logging and capturing unit, is presented.
PatentDOI

Method and apparatus for speaker spotting

TL;DR: In this article, 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 multiple target speaker speech files.