What I need to know about bots - Bucher + Suter
Transcript of What I need to know about bots - Bucher + Suter
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"What I need to know about bots"
Thorsten Schneider, Consultant
Understanding bot technologies
Voice bots and chatbots architectures
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Webinar Series Spring 2020
• March 03, 2020Extensive functionalities with Cisco's smart omni-channel contact centersCisco Contact Center full coverage with live voting and demos. Determine the topics; from the agent desktop strategy to Cloud CC and enriched AI contact centers.
• March 04, 2020Live Vote! Your top 3 Omnichannel Desktop CRM Integration Challenges and how to approach them#Salesforce #Dynamics #ServiceNow #SAP #Oracle #OwnCRM
• March 12, 2020Home Office: Mobile Agent in ActionThis is a technical Webinar. We will demonstrate what the mobile agent function offers and how you can configure it yourself.
• March 19, 2020 | 09:00am
What I need to know about bots.In this webinar, you will learn how voice and chatbots work. What are the differences between them? You’ll learn all about intents and entities. Which solutions are available today?
• March 24, 2020 | 09:00amWhat's new in CCE 12.5?Learn more about Finesse 12.5 features. What is the SMC Cockpit? Do you already know the new “Cisco Analyzer” reporting engine?
• April 02, 2020 | 09:00amWhat's new in the Cisco omnichannel suite? What is Enterprise Chat and Email (ECE)? How can you extend Cisco ECE with more features?
• April 16, 2020 | 09:00amNews around SMC 7.0. Better understand where SMC can help you in your daily business as a supervisor. What is our Supervisor Management Console vision?
-> Please share these webinars with colleagues
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Session recording starts now…
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HousekeepingSession Content
o Please share these webinars with your customer service center colleagues
o Session is recorded
o Slides & recording will be published viawww.bucher-suter.com/news/blog/cisco-cc-webinars/
How to Q&A
o Select the Chat icon from the toolbar at the bottom of your screen
o Ask your question, our experts will answer them quickly
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Agenda
• Understanding Bots
• Chatbot Solutions
• Voice Bot Solutions
• Demo
• Agent A.I. Assistant Services
• Typical Project Approach
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Understanding Bots
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Overview of the process
Input/Output Management Processing
Customer
Channels
Call
Web
Mobile
Video
WebChat
Social
TextAnalytics
Context
Knowledge Management
Analytics
Bot Routing & Agents
Virtual Agent
Human Agent
Bot to human hand-off
Customer Workflow
Universal Queue
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Important Components of a Bot
Component Description
NLU Natural Language Understanding. This component takes text input and can determine the intent of the input and also identify the entities.
Dialog Management incl. Orchestration
Component predicts the next best action/question to identify and fill all entities also using the customer’s backend system. For example, if an entity is not filled, this component will ask a question to get the entity filled. Also it controls the conversation and determines if a handover to a contact center with skilled human agents is needed or “finishes” the request in the backend, without agent intervention.
TTS Text to Speech. This component is used to synthesize the output of the NLP into speech.
ASR/STT Automatic Speech Recognition/Speech to Text. These components are only used in Voice Bots for transforming spoken context into text.
Customers Backend System holding customer data, order processing systems, ERP, CRM etc.
Microsoft LUIS (NLU)
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Components for a Chatbot
Dialog Management & Orchestration
NLU
CustomerBackend
(Customer Data/ Request fulfillment)
Webchat/Social Messaging
connector
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Inside the NLUSpeech Recognition
(ASR)
Co
nten
t/ In
tent
word vectors
sentence vectors!
document vectors!
Context/ DialogOrchestration
Content identification
(NLU)T
extS
ynth
eses
Text to Speech(TTS)
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Example of Dialog Management & NLU
{ "query": "Book me a flight to Cairo",
"topScoringIntent": { "intent": "BookFlight", "score": 0.9887482 },
"intents": [ {}, "intent": "BookFlight", "score": 0.9887482 { "intent": "None", "score": 0.04272597 }, { "intent": "LocationFinder", "score": 0.0125702191 }, { "intent": "Reminder", "score": 0.00375502417 }, { "intent": "FoodOrder", "score": 3.765154E-07 }, ], „
entities": [ { "entity": "cairo", "type": "Location", "startIndex": 20, "endIndex": 24, "score": 0.956781447 } ] }
NLU Processing
Destination: Cairo
Person?
Start airport?
Date/Time?
Customer:
“Book me a flight to Cairo”
Intent: “BookFlight”
Next best question/action:
“OK, you want to fly to Cairo. Where do you want to start?”
Dialog Management
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Natural Language Understanding
Book me a f l ight f rom New York to Budapest today.
Intent: book flight
Entities: Person: Thorsten Schneider, customer ID:118473 (me)
Departure Airport: New York
Destination Airport:Budapest
Flight time: 19.03.2020 (today)
User Authentication
& Transformation through DialogManagement
Entity & Intent Extraction
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New York
- JKF - John F. Kennedy International Airport
- LGA - LaGuardia Airport
- EEA - Newark Liberty
- JRB - Downtown Manhattan Heliport
- QNY - East 34th Street Heliport
- JRA - West 30th Street Heliport
- 6N6 - Evers Seaplane Base
Bot Dialog Management is responsible for
filling the entity “destination”.
It asks predefined questions find the correct
airport out of 188 New York airports
Natural Language UnderstandingEntity & Intent Extraction
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Dialog Management
Book me a f l ight
Departure airport?
Destination airport?
Flight date?
INTENT
QUESTION
QUESTION
VALIDATIONS
CONDITIONS
HELP & INPUT*
CONFIRMATION*
GOAL WORKFLOW
QUESTION
{ Person: Thorsten (me),
Departure Airport: New York,
Destination Airport: Budapest,
Flight time: 19.03.2020}
API search
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Training the NLU Process
Training Material
Data Anonymization (remove names,
adresses, cities etc)
Transf-ormation
from Speech to text
old/existingChat Transscripts
or eMails etc.
Training Material
old/existing Voice Recordings
Elemination of
background noises
Manual Classification
(determine the intent and the
entities)
Train the NLU
Test the NLU
Create a training model & adjust the speech grammar of the ASR engine in order to identify specific product
names etc.
Fine tuningMultiple iterations
New training run
start
Multiple hundreds of training runs needed, usually executed by a subject matter expert within the company
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Entities
Intents
Frontend Training(example from Google Dialogflow)
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Turn the Chatbot into a Voice Bot
Dialog Management & Orchestration
NLU
CustomerBackend
(Customer Data/ Request fulfillment)
ASRTTS
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Chatbot = or ≠ Voice Bot?
NLU
Dia
log
Ma
na
gem
ent &
Orch
estratio
n
Dia
log
Ma
na
gem
ent &
Orch
estratio
n
ASR
TTS
Social Messaging Interface
Customer Backend Data
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Voice Bot Challenges
Challenge Solution
Background noises Audio tuning
Language Dialects Train a Statistical Language Model (SLM)
Understand the correct context Grammar Tuning of the ASR & TTSExample: QR Code ≠ Kuh R Kot
“Eh, Ehm, Hm” and usage of fillwords Identification and removal in Dialog Management
Fast dialog conversations flow, customer answers immediately andunprecised via speech
Dialog Manager must “steer” the conversation, to get precise information
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> N O " O N E F I T S A L L " S O L U T I O N> N O " O F F T H E S H E L F " S O L U T I O N
" A I " I S N O T A S O F T W A R E P R O D U C T
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b+s connects bots with contact centers
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ChatbotSolutions
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Current ChatbotSolutions
• eGain Virtual Assistant for Cisco ECE
• Individual “any” bot integration, based on ECE
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eGain Virtual Assistant for
Cisco ECE
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Bot assistant pops upon customer site
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Handoff the chat frombot to the agent
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Chat Virtual Assistant
eCommerce, Transactional Systems, and Fulfillment
Dialog
Manager
Context
Sentiment
Brand Pref
Intent
Classification
Confidence?
Virtual Assistant
Knowledge
Base
Process
Guidance
Agent escalation
Conversational reasoning
ResolutionMediumLow
High
Advisor
Digital Media
Caller
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Individual Bot Integration into
Cisco ECE
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• New Finesse ECE frontend in CCE 12.0
• Pop-up on incoming chat
• Enable/disable chat button on website
based on agent availability
• Show expected wait time to get to an
agent
• Open API for social messenger
integration and apps
ECE Chat
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Chat BOT Framework
Agent CTI Desktop
NLPTranslation Services
Chat BOT Orchestrator
CRM
Webchat
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Voice Bot Solutions
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Current Voice Bot Solutions• SemanticEdge
• Microsoft LUIS
• Google Dialogflow
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SemanticEdgeVoice Bot
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Voice Bot Processing
Calling
Person
Automatic
Transcription
TranscriptionEngine
Text
Manual “post”
transcription and
“post” classification
Statistic AI
classification
DeepLearningClassifier
DeepLearning
NLU
SLM
Text
Source: SemanticEdge
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Microsoft Cognitive Services
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Voice Bot
using Microsoft LUIS connected via AudioCodes AI Gateway
Agent CTI Desktop
Cisco CVP
Cisco CCE
Escalate Call to agent
with extracted information from
botConsolidated Routing & Reporting Finesse
Customer calling
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Cisco “Conversational
IVR”
based onVVB 12.5 Integration with Google Dialogflow
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Voice Bot
Conversational IVR with CCE 12.5
Agent CTI Desktop
Cisco CVP
Cisco CCE
Escalate Call to agent
with extracted information from
botConsolidated Routing & Reporting Finesse
Customer calling
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DEMOGoogle Dialogflow Voice Bot
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Agent A.I.AssistanceServices
• Cisco Answers
• Audio transcriptions for quality assurance & data analysis
• Chat & Voice translational services
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Cisco Answers providesthe agent knowledgearticles based on the
the voice conversation
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The Finesse “VoiceaIntegration” provides a
transscript of the conversation to the
agent
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Google Translatecloud serviceprovides chat
translation services
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Google Translatecloud serviceprovides chat
translation services
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Project Approach
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Typical project course in data science projects
Iterative Workflow
project launch
Vagueness,
descreasing with
project progress
SolutionMeasureable,
partial results
Scope for
decision making
Actual course
of project
Initally
anticipated
solution
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decision gate
Bot design documentation
Proof of Concept(PoC) build-up
Bot use case design workshop
decision gate
Test in production& PoC fine-tuning(multiple Sprints)
Productionfinalization
& integration
Project management, reporting, feedback and documentation
From wish to solution…
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Where to start….?
• Many bots consume cloud services, initiate the data security approval within your
company to become “cloud ready”.
• Collect data for the bot training and classify the data.
• Tagged/classified chat transcripts
• Tagged/classified emails
• Frequently asked questions (FAQ) lists
• Knowledgebase articles
• Create a business case for your bot use case to justify the new technology.
• Allocate IT budget for:
• pilots and innovation proof of concepts.
• the production rollout itself.
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Webinar Series Spring 2020
• March 03, 2020Extensive functionalities with Cisco's smart omni-channel contact centersCisco Contact Center full coverage with live voting and demos. Determine the topics; from the agent desktop strategy to Cloud CC and enriched AI contact centers.
• March 04, 2020Live Vote! Your top 3 Omnichannel Desktop CRM Integration Challenges and how to approach them#Salesforce #Dynamics #ServiceNow #SAP #Oracle #OwnCRM
• March 12, 2020Home Office: Mobile Agent in Action.
This is a technical Webinar. We will demonstrate what the mobile agent function offers and how you can configure it yourself.
• March 19, 2020 | 09:00amWhat I need to know about bots.In this webinar, you will learn how voice and chatbots work. What are the differences between them? You’ll learn all about intents and entities. Which solutions are available today?
• March 24, 2020 | 09:00am
What's new in CCE 12.5?Learn more about Finesse 12.5 features. What is the SMC Cockpit? Do you already know the new “Cisco Analyzer” reporting engine?
• April 02, 2020 | 09:00amWhat's new in the Cisco omnichannel suite? What is Enterprise Chat and Email (ECE)? How can you extend Cisco ECE with more features?
• April 16, 2020 | 09:00amNews around SMC 7.0. Better understand where SMC can help you in your daily business as a supervisor. What is our Supervisor Management Console vision?
-> Please share these webinars with colleagues
![Page 52: What I need to know about bots - Bucher + Suter](https://reader031.fdocuments.net/reader031/viewer/2022012021/61689e30d394e9041f71311d/html5/thumbnails/52.jpg)