Analyzing Call Data Through Live Calls Using Sphinx Tool
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2018-08-24 https://doi.org/10.14419/ijet.v7i3.31.18273 -
Analysis, Big data, Live Calls, STT, Sphinx. -
Abstract
For Improving the Business growth, the Business people try to know the customer's intension about their products. One of the best methods of collecting customer's feedback is telephone or mobile survey where customer service representatives(CSR) can interact with customers through phone calls and also record to analyze the customer's call data. The main issue of call data analysis through recorded files is a large amount of storage is required to store the audio files. This results increased costs, maintaining the hardware and software systems and manage a database system. In this paper we can directly convert the live calls into text files using speech to text (STT) algorithm and analyze these text files using Hadoop and MapReduce Framework for improving their future purchasing behavior.
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References
[1] https://en.wikipedia.org/wiki/Speech.
[2] https://en.wikipedia.org/wiki/Speech_recognition.
[3] http://searchcrm.techtarget.com/definition/speech-recognition.
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[8] Willie Walker, Paul Lamere, Philip Kwok, Bhiksha Raj, Rita Singh, Evandro Gouvea, Peter Wolf, Joe Woelfel, "Sphinx-4: “A flexible open source framework for speech recognition", (2004).
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[11] http://www.gavo.t.utokyo.ac.jp/~kuenishi/java/sphinx4/edu/cmu/sphinx/frontend/FrontEnd html.
[12] https://cmusphinx.github.io/doc/sphinx4/javadoc/edu/cmu/sphinx/linguist/Linguist.html.
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How to Cite
V. Krishnam Raju, K., & N. S. Manaswini, V. (2018). Analyzing Call Data Through Live Calls Using Sphinx Tool. International Journal of Engineering & Technology, 7(3.31), 93-97. https://doi.org/10.14419/ijet.v7i3.31.18273Received date: 2018-08-25
Accepted date: 2018-08-25
Published date: 2018-08-24