its an article based on my research which is on IoT

1. MISSION
CHRIST is a nurturing ground for an individual’s holistic
development to make effective contribution to the society in
a dynamic environment
VISION
Excellence and Service
CORE VALUES
Faith in God | Moral Uprightness
Love of Fellow Beings
Social Responsibility | Pursuit of Excellence
Customer Service using Artificial Intelligence-
based VoiceBot using Automated Interactive
Voice Response System
By
Neil Manoj C (2247224)
II MCA-B
Department of Computer Science,
CHRIST (Deemed to be University), Bangalore Central Campus
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Agenda
● Introduction
● Literature Review
● Findings from literature review
● Research Gaps
● Need for the study
● Objectives
● Social Impact
● Conclusion
● References
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PROBLEM STATEMENT
● By 2024, consumer retail spending via chatbots worldwide will reach
$142 billion—up from just $2.8 billion in 2019?
Source : FORBES MAGAZINE
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Introduction
● Voicebots are software powered by Artificial Intelligence (AI) where callers
can navigate an Interactive voice response (IVR) system with their voice.
● Voicebots are advantageous for less-literate population. The question-
answering system is trained on data acquired from the IVR platform on
which users can record questions which is moderated and sent to experts for
answers.
● A conceptual framework of firm capabilities was described where it enable
firms to operate with ‘one voice’ for a reliable interaction.
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● Voicebots used as domain-specific automated question answering system
may provide a better user-friendly means of information search than
keyword based search.
● AI-enabled automated Voicebot system no longer only convey messages
between people, but are now acting as a communication partner themselves.
● Similarly, a banking bot project is built using AI algorithms that analyze
user’s queries and understand the message. The dataset contains bank-
related queries and answers. The system recognises the user’s query and
answers them appropriately.
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Introduction

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Literature Review
[1] C.O. Sarath ‘VIRTUAL BANK ASSISTANCE: AN AI BASED VOICE
BOT FOR BETTER BANKING’ [ Year-2020]
● This article is about ai based voice bot for better banking that uses AI
majorly ML to have a conversation with humans. Users can ask questions,
make requests and respond to chatbot questions and statements using natural
language.
● A banking bot project is built using Artificial Intelligence algorithms that
analyze the user‘s queries and understand the user‘s message.
● The system is designed for banks to use where users can ask any bank related
questions like loan, account, policy, etc which are bank related queries.
● The system recognizes the user‘s query and understands what he wants to
convey and simultaneously answers them appropriately.
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Literature Review
[2] R.S. Rohit and R. Gaurav ‘INTERACTIVE VOICE RESPONSE
USING AUTOMATIC SPEECH RECOGNITION TECHNIQUES FOR
CALL CENTERS’ [Year-2018] [Scopus Indexed]
● This paper explains the use of emotion recognition techniques to identify if
the customer are satisfied the ASR(Automatic speech recognition) system’s
performance.
● This paper presents approaches and techniques for how automatic speech
recognition can improve the user experience and save capital in operations of
call centre.
● Implementation: Amazon Lex and Amazon Connect
● Artificial intelligence and deep learning pattern classification provides deep
insights in ASR(Automatic speech recognition) system. Artificial
intelligence and Deep Learning allow the computer system to keep a watch
and identify probably fraudulent or inappropriate behavior of the customer
care executive.
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Literature Review
[3] S. Jagdip et al. ‘ONE-VOICE STRATEGY FOR CUSTOMER
ENGAGEMENT’ [Year-2020]
● This article develops a conceptual framework of firm capabilities that enable
firms to operate with “one voice” to deliver seamless, harmonious, and
reliable interactions across diverse interfaces in a customer journey.
● The proposed framework integrates three themes:
• service interaction space
• learning and coordination
• one-voice strategy
● The key elements of all the three frameworks proposed in this article—SIS,
intelligence generation/use capabilities, and one-voice strategy—and
developing models that incorporate both mediating mechanisms and
moderating contextual factors.
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Literature Review
[4] K. M. Kate et al. ‘Mediated Communication and Customer Service
Experiences: Psychological and Demographic Predictors of User
Evaluations in the United States’ [Year-2020] [Scopus Indexed]
• Media richness theory asserts that the more cues/information a communication
channel has, the more it is able to reduce uncertainty and ambiguity.
● Research focused on communication channels’ different attributes and the
extent to which they could transmit types of information.
● Research also found that people’s experience, communication apprehension
and innovativeness influenced their perceptions of the different modalites in
the customer service.
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Literature Review
[5] B. Pranav et al. ‘Initial Lessons from Building an IVR-based Automated
Question-Answering System’ [Year-2020] [Scopus Indexed]
● A large database of questions and answers were curated, and the goal was to
use this database to build an automated FAQ retrieval system so that questions
can be answered automatically and instantly.
● Users tend to provide their personal, non-relevant details and this accuracy
loss is removed by benchmarking the voice-recording against the annotated
dataset to separate out the non-relevant portions.
● The feasibility of using IVR systems for voice input which is of lower audio
quality was evaluated.
● The database is kept in a FAQ retrieval format rather than in a conversational
format. The query is matched and the appropriate answer is returned. With
each experiment conducted, the question is captured in different ways and the
answer is recorded and mapped.
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Findings on Literature Review
● The Artificial Intelligence-based services include services like automatic
checkbook re-order facility, etc, banks internally use them for employees
performance evaluation, credit evaluation of customers, etc and products like
customized investment advice for customers after for their portfolio analysis
and customized investment solutions after evaluation the credit history as
well as income pattern.
● They can give customers information on their accounts and help them make
credit card payments from their smartphones.
● Bots analyze the expenditures of the customers and help them in increasing
their rewards and savings by giving suggestions.
● ASR system: ASR system uses modern AI and Deep Learning techniques to
train itself to improvise. This model works on the server less architecture
enabling it to use less disk and storage.
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Findings on Literature Review
● Companies are attempting to cut costs and improve customer satisfaction by
turning to automated systems such as Interactive Voice Response. The system
helps offload customer service tasks. Customers need time to trust the
automated modalities, but with improved media richness and repeated usage,
the shortcomings on Voicebots will be removed.
● In terms of individual characteristics, customers are more willing to interact
with the automated modalities simply because they are willing to find solutions
for themselves, regardless of the interface provided.
● On performing experiments, it was found that the automatically generated
transcripts did not perform without the manually transcribed and curated data.
Greater success was received after eliminating unnecessary information from
the questions and answers. Further, clearer answers were given when the
search space was restricted by asking users to select the broad theme of interest
to them.
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Research Gap
● The customers prefer using humans over automated IVRs and Voicebots as
they want human empathy in the interaction. They have no power in the
interactions.
● Use of Voicebots in clinical psychology, and mental health – series of
questions need to be asked only on the customer’s consent.
● Many customers have low expectations in the self-service voicebot offered
by banks. Some self-service transactions result in the customer having to
contact the call centre.
● Use of AI and Deep Learning to allow the system to watch and identify
fraudulent, inappropriate behavior in the communication.
● Voicebot systems perform well in English speaking countries. But, taking
developing countries such as India where multiple languages are spoken, the
model is difficult to implement. In addition, many people are illiterates.
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Need for the research
● Need to research how people perceive different modalities for accessing
information to solve problems of their personal needs.
● Need to reduce uncertainty and ambiguity in the communication. Media
richness should be explored with regards to automated technology.
● Need to narrow the search space by asking customers to specify the question
more in detail and ask crisp questions without having too many unnecessary
information. Otherwise, filtering out the unnecessary questions can be done
through technology.
● Reducing the average handling time and offering better outcomes through
Intelligent Virtual Assistant (Voicebots using IVR) in business-customer
interaction.
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STATISTICS
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WHO IS BETTER?
Voicebot or Chatbox?
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Social Impact
• Integrating voicebots with IVR cab improve user experience and save capital
in operations of call centres.
• Reducing waiting time and clearing most queries of the customers
immediately in banking, health and other fields.
• Customer and businesses can interact across the customer journey, making
economy in business better.
• Modern technologies such as AI, automation and robotics are profoundly
expanding in all areas, therefore bringing advancement in society.
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Conclusion
• Before building the theory for IVR and Voicebots, we need to understand the
people’s perception and reactions to these type of technology.
• Businesses can do more for the customer than just respond with simple basic
logic. In banking system, voicebots can give information based on their
accounts and assist them in making payments from their smartphones.
• Before the conversation between the user and customer is initiated, the
customer needs to answer simple questions for user personalisation. This
way, voicebots can pick out the answers which the customer might expect.
• By identifying the customer satisfaction level using the system, organisations
can perform better in their daily operations.
• One-voice strategy helps in configuration of learning and coordination
capabilities to meet the conditions for effective customer engagement.
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References
[1] Mandal, M. (2020). ISSN NO : 2236-6124 VIRTUAL BANK ASSISTANCE : AN AI BASED
VOICE BOT FOR BETTER BANKING Page No : 177 ISSN NO : 2236-6124. IX(2236), 177–
184. https://doi.org/10.13140/RG.2.2.21535.10405
[2] Sehgal, R. R., & Raj, G. (2018). Interactive Voice Response Using Automatic Speech
Recognition Techniques for Call Centers. SSRN Electronic Journal, 662–667.
https://doi.org/10.2139/ssrn.3170200
[3] Singh, J., Nambisan, S., Bridge, R. G., & Brock, J. K. U. (2021). One-Voice Strategy for
Customer Engagement. Journal of Service Research, 24(1), 42–65.
https://doi.org/10.1177/1094670520910267
[4] Mays, K. K., Katz, J. E., & Groshek, J. (2020). Mediated communication and customer service
experiences: Psychological and demographic predictors of user evaluations in the United States.
Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-
Janua,pp.2761-2770,2020, https://doi:10.24251/hicss.2020.337
[5] (Bhagat et al., 2020)Bhagat, P., Prajapati, S. K., & Seth, A. (2020). Initial Lessons from Building
an IVR-based Automated Question-Answering System. ACM International
Conference.Proceeding Ser.,2020.doi:10.1145/3392561.3397581
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