Abstract
Voice-based call centers enable customers to query for information by speaking to human agents. Most often these call conversations are recorded by call centers with the intent of trying to identify things that can help improve the performance of the call center to serve the customer better.
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References
VERINT, Speech analytics essentials for audiolog, http://www.verint.com/solutions/enterprise-workforce-optimization/products/speech-analytics/impact-360-speech-analytics-essentials-for-audiolog
S.K. Kopparapu, I. Ahmed, Enabling rapid prototyping of an existing speech solution into another language, in 14th Oriental COCOSDA Conference, Oct 2011
M.A. Pandharipande, S.K. Kopparapu, A novel approach to identify problematic call center conversations, in Computer Science and Software Engineering (JCSSE), 2012 International Joint Conference on, 30–1 June 2012, pp. 1–5
M.A. Pandharipande, S.K. Kopparapu, Real time speaking rate monitoring system, in Signal Processing, Communications and Computing (ICSPCC), 2011 IEEE International Conference on, sept. 2011, pp. 1–4
H. Takeuchi, L.V. Subramaniam, T. Nasukawa, S. Roy, Automatic identification of important segments and expressions for mining of business-oriented conversations at contact centers, in Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), 2007
G. Mishne, D. Carmel, R. Hoory, A. Roytman, A. Soffer, Automatic analysis of call-center conversations, in Proceedings of the 14th ACM International Conference on Information and Knowledge Management, CIKM ’05, New York, USA, 2005, ACM, pp. 453–459
V. Pallotta, R. Delmonte, L. Vrieling, D. Walker, Interaction mining: the new frontier of call center analytics, in 5th International Workshop on New Challenges in Distributed Information Filtering and Retrieval, 2011
G. Zweig, O. Siohan, G. Saon, B. Ramabhadran, D. Povey, L. Mangu, B. Kingsbury, Automated quality monitoring for call centers using speech and nlp technologies, in Proceedings of the 2006 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Companion Volume: Demonstrations, NAACL-Demonstrations ’06, Stroudsburg, PA, USA, 2006, Association for Computational Linguistics, pp. 292–295
F. Cailliau, A. Cavet, Mining automatic speech transcripts for the retrieval of problematic calls, in Proceedings of the 14th International Conference on Computational Linguistics and Intelligent Text Processing—Volume 2, CICLing’13, Berlin, Heidelberg, 2013, Springer, pp. 83–95
S.K. Kopparapu, M.A. Pandharipande, G. Sita, Music and vocal separation using multiband modulation based features, in Industrial Electronics Applications (ISIEA), 2010 IEEE Symposium on, Oct 2010, pp. 733–737
S.K. Kopparapu, A. Imran, G. Sita, A two pass algorithm for speaker change detection, in TENCON 2010–2010 IEEE Region 10 Conference, nov. 2010, pp. 755–758
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Kopparapu, S.K. (2015). Case Study. In: Non-Linguistic Analysis of Call Center Conversations. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-00897-4_5
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DOI: https://doi.org/10.1007/978-3-319-00897-4_5
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