Email this article 
Open Access
Subscription or Fee Access
Applying Voice Analytics in Contact Centre Services
Abstract
Voice Analytics is a new emerging trend in the market which focuses on analyzing the spoken content of the voice and extracting valuable information from the spoken content. Voice Analytics refers to the process of analyzing the speech signal,extracting the features and dwelling more insight into the signal to understand what is being spoken. The aim of this project is to develop a comprehensive Voice Analytics System for an Enterprise which will be used by the Management in arriving at Management decisions. The system is developed for an insurance industry which can be deployed in the call centre of any insurance industry. This is the low computation cost based system which can be deployed in call centres of any industry kind.
Keywords
References
A telephone speech recognition system using word spotting technique based on statistical measure, Kimura, T. Niyada, K. Hiraoka,S. Morii, S. Watanabe, T
T.V.Geetha and Rajeswari Sridhar, “Feature Extraction for Music Information Retrieval of Carnatic Music Songs”, pp1-5
Martin McKinney and Jeroen Breebart, “Features for Audio and Music Classification”, ISMIR 2003, pp 3-6
Annamaria Mesaros and Jaakko Astola, “The Mel Frequency Cepstral Coefficients in the Context of Singer Identification”, pp 1-2
White Paper on “Autonomy Enterprise Speech Analytics” by Autonomy Inc. and Autonomy Systems Ltd, Edward Bridges, pp. 3-5
White Paper on “Customer Interaction Analyser” by CISCO, pp. 1-3
Bachu R.G., Kopparthi S.,Adapa B. Barkana B.D., “Separation of Voiced and Unvoiced using Zero crossing rate and Energy of the Speech Signal”, December 2006, pp 4,5.
M.J. Hunt, “Spectral Signal Processing for ASR”, Proc ASRU’99, Dec 1999, pp-1,2
Noise reduction and increased VAD Accuracy Using Spectral Subtraction, Jeffery J. Faneuff and Dr. D. Richard Brown III, pp 2,2006
Aaron Herrnstein, “Start/End Delays of Voiced and Unvoiced Speech Signals”, U.S. Department of Energy, September 24, 1999, pp 5-7
S.B. Davis and P. Mermelstein “Comparison of parametric representations for monosyllabic word recognition in continuous spoken sentences”, IEEE Trnas. Acoust., Speech, Signal Processing, pp.357-366, vol 28, Aug. 1980.
Liang Gu and Kenneth Rose, “Split-band Perceptual Harmonic Cepstral Coefficients as Acoustic Features for Speech Recognition”, February2002, pp 1,2.
Rabiner and B.H. and B-H. Juang. Fundamentals of Speechrecognition,PTR Prentice Hall, Englewood Cliffs New Jersey,1993
D. L.Wang, “Feature-based speech segregation,” in Computational Auditory Scene Analysis: Principles, Algorithms, and Applications, D.L. Wang and D. L. Wang and G. J. Brown, Eds. New York: IEEE Press, 2006, pp.81–114, (dual imprint with Wiley).
D.L Wang and G. J. Brown, “Separation of speech from interfering sounds based on oscillatory correlation,” IEEE Trans. Neural Netw., vol. 10, no. 3, pp. 684–697, May 1999
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.