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Speaker Identification of Customer and Agent using AWS

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Speaker Identification of Customer and Agent using AWS


G. Satyanarayana | Dr. Bhuvana J



G. Satyanarayana | Dr. Bhuvana J "Speaker Identification of Customer and Agent using AWS" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3, April 2020, pp.997-999, URL: https://www.ijtsrd.com/papers/ijtsrd30753.pdf

As everyone knows that Sentimental analysis plays an important role in these days because many start-ups have started with user-driven content [1]. Only finding the voice is not be the real time scenario so finding the Sentiment analysis of agent and customer separately is an important research area in natural language processing. Natural language processing has a wide range of applications like voice recognition, machine translation, product review, aspect-oriented product analysis, sentiment analysis and text classification etc [2]. This process will improve the business by analyze the emotions of the conversation with respect to the customer voice separately and also agent voice separately. In this project author going to perform speaker identification and analyze the sentiment of the customer and agent separately using Amazon Comprehend. Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to extract the content of the voice. By using the speaker identification author can extract the unstructured data like images, voice etc separately so it is easy to analyze the business performance. Thus, will identify the emotions of the conversation and give the output whether the customer conversation is Positive, Negative, Neutral, or Mixed. To perform this author going to use some services from Aws due to some advantages like scaling the resources is easy compare to the normal process like doing physically such as support vector machine (SVM). AWS services like s3 is a object data store, Transcribe which generate the audio to text in raw format, Aws Glue is a ETL Service which will extract transform and load the data from the S3, Aws Comprehend is a NLP service used for finding sentiment of audio, Lambda is a server less where author can write a code, Aws Athena is a analyzing tools which will make complex queries in less time and last there is quick sight is a business intelligent tool where author can visualize the data of customers and also agents.

Sentimental analysis, NLP, Speaker identification, S3, Transcribe, Aws Glue, Aws Comprehend, Lambda, Athena, Quick sight, ETL


IJTSRD30753
Volume-4 | Issue-3, April 2020
997-999
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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