E. A. Stepanov, B. Favre, F. Alam, S. A. Chowdhury, K. Singla, J. Trione, F. B'echet, G. Riccardi
IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2015), Scottsdale, Arizona, USA, 2015
Publication year: 2015

ABSTRACT

This paper presents the SENSEI approach to automatic summarization which represents spoken conversation in terms of factual descriptors and abstractive synopses that are useful for quality assurance supervision in call centers. We demonstrate a browser-based graphical system that automatically produces these summary descriptors and synopses.

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