Transcript UIM Focus Areas 2007

®
Speech Technology Opportunities and
Challenges
David Nahamoo
Speech CTO, IBM Research
Dec 12, 2006
Needs for Speech Technology
Value
Ease of use
Speed, efficiency
Extended reach
Devices
USABILITY
Multimodal
Interaction
Dictation
Transactional
Information
Access
Command &
control
Commerce
AUTOMATION
Voice
Web
Information
GLOBAL ACCESS
Multimedia
Analytics
Transcription
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Multichannel
Self-Service
Value
Lower cost
Increased cust sat
From cost to revenue
Problem solving
Value
Integration of voice/video with
enterprise data
Indexing of large amount of
multimedia info
Breaking language barriers
Accessibility
Major Speech Application Opportunities
 Commerce
– Contact Centers
– Unified Communication
 Global Access
– Speech To Speech Translation
– Translingual MultiMedia Mining
– Accessibility
 Devices
– Automotive
– Set Top Box
– Mobile Phones
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Speech Technology Innovation that Matters
• Conversational Interaction
–
Dealing with Complexity
• Speech Analytics
–
Extracting Insight / Knowledge
• Multilingual Dimension
–
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Globalization
®
Contact Centers Of Future
Contact Centers face a number of challenges as they attempt to
balance costs, customer experience and revenue growth
1. Cost Reduction/
Containment
BUT…
Too much focus on Cost Reduction
2. Customer Experience
Improvement
BUT…
Too much focus on the Customer
Experience
Can actually lead to…
Can actually lead to…
Limits on
Revenue
Growth
Limits on
Revenue
Growth
Poor
Customer
Experience
Rising
Costs
3. Revenue Growth
BUT…
Too much focus on Revenue
Growth
Can actually lead to…
Poor
Customer
Experience
Rising
Costs
Differing emphasis can be placed on each one, but
unless managed carefully and balanced effectively for
the business, the effects can be disastrous…
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Contact Centers – Logical Components and Focus Areas
Back-end business processes, applications and information services (internal and external)
Systems
CRM
Information
ERP
MDM
SCM
Channel Services – Self-service
Analytics
ODS
EDW
ECM
QAM
UIM
KPIs
Search
KM
RTA
Agent Desktop
Portal
Alerts
Dashboards
Agent Services
Outbound
Presence
Skills
WFM
Voicemail
Email
Chat
Voice
Data Services
Web
Services
Contact
Services
Universal
Queue
Routing
Voice
Callback
Channel Services - Assisted
Mail
Web
Voice
Chat
Email
Voicemail
Video
Network Services
Public Internet
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Managed IP Network
Dialer
VoIP Gateway
Fax
Contact Centers – Logical Components and Focus Areas
Back-end business processes, applications and information services (internal and external)
Systems
CRM
Analytics
Information
Analytics
Information Integration
ERP
MDM
SCM
Channel Services – Self-service
Self Service
ODS
EDW
ECM
QAM
KPIs
KM
Portal
Alerts
Outbound
Skills
WFM
Voicemail
Email
Chat
Voice
Agent Performance
Contact
Universal
Queue
Services
Routing
Voice
Callback
Channel Services - Assisted
Web
Voice
Email
Voicemail
Dialer
Revenue
Growth
Chat
Video
Network Services
Managed IP Network
Services
Mail
Multi-channel Access
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RTA
Dashboards
Agent Services
Public Internet
Search
Agent Desktop
Presence
Data Services
Web
UIM
VoIP Gateway
Fax
®
Self-Service
Increased Self-Service
 Self-service to 80% levels and higher is possible in at least some centers
– Today’s contact centers are typically 10 to 20% self-service in most industries, but at
least some companies claim 80% self-service now where Web-based interaction
predominates; when voice predominates, numbers are much lower
– Live-agent costs are an order of magnitude higher than the costs of self-service
 Self-service adoption has been slow to take off (8% growth 2003-2005)
– Self-service is more challenging technically than agent performance because of the
difficulty of achieving high customer satisfaction
– Self-service is often run by another group than the one that runs the contact center
– Self-service will be the end-game as labor-arbitrage becomes increasingly more difficult
 Whichever vendor develops ways to drive self-service fastest (while
maintaining customer satisfaction) will have a commanding position in the
marketplace
– Self-service is clearly a huge cost-savings opportunity
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Customers prefer the convenience and control aspect of
self-service, and have high expectations
 Customers prefer self-service
– Self-service preferred for many types of customer
contact
•
•
•
•
Viewing Bill (42%);
Checking Minutes (44%);
Checking/Changing a Talkplan/package (37%);
Subscribing to Services (38%)
– Web preferred to the phone (50%)
•
Provided one can obtain answers in the same amount of
time
“How important was the ability to serve yourself (as a customer) in your decision
to use the service provider in the first place?”
60%
Very
important
40%
Quite
important
20%
Not very
important
0%
Not at all
important
20%
40%
60%
Mobile
 And their expectations are very high
– Ease of use
•
86% indicate they would stop using an organization if
their IVR was difficult to use
– High level of service
•
82% indicate lower level of service via the web
unacceptable
– Majority indicate they would abandon a web
transaction or go to a competitor due to usability
issues.
Source: Fujitsu Consulting and Netonomy, Modalis Research Technologies, Genesys, Inc.,
Harris Interactive
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Bank
Health insurance
Household
insurance
IVRs are still the dominant self-service channel and they are
increasingly becoming speech-enabled
 IVRs are still the dominant contact
channel
– 45% of contact starts in IVR channel
IVRs are becoming speechenabled
– Speech-enabled IVRs support more
complex functionality and higher
completion rates
• Well-designed voice user interfaces (VUI)
can reduce call time by as much as 30% and
compared to traditional IVR systems and cut
opt-out rates by 50% (Forrester - 2003)
• Increased IVR retention rate. Companies are
up to 60% more likely to retain a caller within
the IVR using speech vs. touch tone (Giga)
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Conversational Interaction
 Should support the gap between user mental model
and the application model
– Task Complexity
– User Familiarity
– User Patience
 Should minimize the user effort and task completion
time
– Consistent
– Rapid
– Efficient
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Conversational Solutions
INFORMATIONAL
PACKAGE
TRACKING
STOCK
QUOTE
FLIGHT
STATUS
LOW
TRANSACTIONAL
BANKING
CALL ROUTING
STOCK
TRADING
FLIGHT
RESERVATION
TRAVEL
MEDIUM
COMPLEXITY
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PROBLEM SOLVING
CUSTOMER
CARE
TECHNICAL
SUPPORT
HIGH
User and application models match,
Time not a factor, No decision making
PACKAGE
TRACKING
STOCK
QUOTE
String of numbers & characters + checksum ASR
Large list of names and symbols ASR
User model is close to application,
Some decision making, Time not a factor
BANKING
STOCK
TRADING
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Directed Dialog and limited syntax NLU
User’s model might not match application’s,
Involved decision making, Time a factor
TRAVEL
Substantial Dialog (& Language Understanding)
User and application models match,
No decision making, Long list of concepts
CALL ROUTING
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Substantial Language Understanding
Conversational Help Desk Challenges
Help Desk is the most complex of all three
types of conversational speech applications
Complexity is based on Nature of the Call
• User domain model is limited at best
• User is usually upset
• Complex dialog and language understanding
Current Market Solution
• No Industry “best practices” have been established
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Overview of IBM Help Desk
Incoming
Calls
Main Menu
Workstation, host, password, business app, telephone
Troubleshooting
Create Trouble
Ticket
Self service
(telephone)
0.5% to 3%
Introducing ( Audrey )
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Agent handles
97-99.5% of calls
80% Service
is HOWTO
Password Reset
Self Help
(FAQ/HOWTO)
Not-entitled
®
Speech Analytics
Contact Center Analytics
Contact Points
Enterprise
Customer
Branch
office
Web
Agent
Self Service
Call
Center
Analytics enhances
value for:
Products
& Services
IVR
Structured
Unstructured
Structured
Agent
Data
Call logs & transcripts
Emails, Surveys
Customer/Product
Transaction Data
 Self-service
 Agent performance
 Cross-sell/up-sell
Integrate & Analyze Structured
& Unstructured Data
 Transformational
Diagnostics
 Business Intelligence
 Marketing
 ……
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Analyze Agent Performance
Instant Market Intelligence
Improve C-Sat, Upsell Rate

Analyze Contact Drivers

Improve FAQs, Web pages



Customer preferences
Dissatisfaction Drivers
Lifetime Value Management
Call Center Operation Quality
Millions of Calls Everyday
 Want general information:
– Are callers happy?
– Are processes followed?
– What are people asking for?
– What is the trend of occurrence of
known problems?
– Are there new problems?

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Need to know where to take action:
– Save a customer from defecting
– Apologize for mishandled calls
– Show call to agent for coaching
– Follow up on a missed sales
opportunity
Currently
 Human monitoring is necessary for
these things
 Only a small fraction of calls can be
checked
 Most checking is wasted
 There is no permanent record of the
calls
Speech Analytics for Automated Quality Monitoring
Background:
– IBM NA call center team listens to and
evaluates ~1% of all calls
Extract audio
from CM/DB2
Turn Audio into Text
UIMA Processing Pipeline
Collection Reader
From CM
Speech-to-Text Annotator
– 35 questions answered
Evaluate Calls
Analytics Annotators
• “did the agent use courteous words and
phrases?”
Store Analysis and
CAS Consumer
• “did the agent speak in an appropriate tone?”
Transcripts back
• “did the agent follow the closing procedure?”
into CM/DB2
Transcribed & Analyzed audio
• “did the agent solve the problem?”
Websphere
– Mostly random calls, rarely interesting
– Typical of all call centers
CallRank Quality Monitoring Application:
– Monitor 100% of calls
– Answer questions and assign default
ratings
– Provide a ranked list to human monitors to
focus attention on bad calls
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CallRank
Calls &
Stored
Analysis
CM
audio
IBM Call
Centers
Example of a good call
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Example of a bad call
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Automated Quality Monitoring
• Status:
Three times as many bad calls found for same listening effort
Processing ~ 3000 calls/day now from all North American centers
• Technology:
 Answer many questions with pattern matching on decoded text
 Did the agent follow the appropriate closing script?
 Search for “THANK YOU FOR CALLING”, “ANYTHING ELSE”,
“SERVICE REQUEST”
 Use other linguistic cues to improve the accuracy of the system
 Number of hesitations (UH, UM, HUM, etc), total silence, longest
silence, …
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®
Agent Performance
Agent Performance
 Personnel costs are by far the largest component of existing contact center costs
–
Move to off-shore operations has resulted in significant (up to 75%) labor cost reductions
–
Large contact centers have very large numbers of personnel
–
Estimated 6M agents in U.S. in 2004 and continuing to grow
 Even with the rise of self-service, a percentage of calls will still be handled by live
agents
 Numerous opportunities exist to improve performance by automation:
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–
Integration of systems across the business for use in the contact center
–
On-boarding process (e.g., accent monitoring)
–
Training (on-boarding, continuing education, real-time training)
–
Agent quality monitoring
–
Call logging (30% of agent time in some contact centers)
–
Helping the agent find the answer to the customer’s question
–
Workforce management
–
Intelligent call routing globally
–
Expert “multi-channel” agents
–
Activity-centric computing and other collaborative projects
Agent Performance: Voice Assessment/Training
Increased number of off-shore centers

e.g., India (>50% growth)
Key focus in off-shore contact centers

Hiring
–

Shrinking candidate pool and high agent attrition
rates
Training
–
Train agents to have neutral accents to improve
customer experience
Voice Assessment/Training System

Candidate screening for
–
–
–

Accent training
–
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Grammar
Pronunciation
Spoken language comprehension
Correctness of pronunciation, intonation, speaking
rate and syllable stress
Contact Centers Summary
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
Contact centers are focal points in an enterprise from which all customer
contacts are managed

Contact Centers face a number of challenges as they attempt to balance
costs, customer experience and revenue growth

Customers increasingly prefer self-service and speech self-service is now
ready for prime time

Enterprises can achieve improved agent performance with agent productivity
tools and agent hiring/training tools

Enterprises should focus on revenue growth transforming their contact
centers from cost centers to profit centers

Customer demand for choice, convenience and consistency is driving the
adoption of multi-channel enablement in contact centers

Actionable intelligence from real-time and offline analytics of structured and
unstructured customer interaction data will lead to new opportunities for cost
reduction, revenue growth and improved customer experience
®
Increasing Global Reach
Global Language Barriers
Different languages spoken by people living in different regions
or even by different ethnic groups living in the same region
 Language barriers cause…
– High cost for agents – need both subject matter expertise and
language skills
• Call centers, insurance agents, etc.
– Unreachable to broad international business or tourism travel market
– Life threatening in
• medical emergency
• natural disaster situations
• military
– Multilingual on demand media and entertainment
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Data Point: Online population language Mismatch
*
Mismatch:
Diversity of languages spoken online increasing,
yet language of web pages are consolidating
*Global Internet Statistics (http://www.glreach.com/globstats/index.php3)
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*
Multimodal Multimedia Translingual Access
Content
Multimodal
Access
Audio
Speech
Recognition
Transcription, biometrics, …
Video
Multimedia
Analytics
Informational
&
Transactional
Multimodal
Translingual
Access
Translingual
Access
OCR
Multimedia
Translingual
Analytics
Information
Analytics
Context
Image
Translingual
Analytics
Text mining, Categorization, Taxonomies, Entity extraction, Entity relation, Ontology, …
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Text
Machine
Translation
S2S Translation call for innovation
 Speech Recognition Challenges
– Needs to work in noisy environments, with spontaneous, conversational speech
in multiple languages, could be emotional speech when under stress.
 Translation has to handle output of ASR system
– Recognition errors
– Spoken language: different from written language
• Non-grammatical disfluencies
• Imperfect syntax
• Lack of formal characteristics of text: no punctuation or paragraphing
 Translated text must be "speakable" for oral communication
– not enough to translate content adequately; output must be fluent
– Need to carefully consider and tune interactions between ASR, MT and NLG –
need access to all components
 Cost-effective development of new languages and domains
 Intonation translation remains a grand challenge
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Speech Technology Driving New
Business Opportunities
•
Increasing Self Service: More natural
interaction with more difficult tasks is made possible
•
Increasing Agent Productivity, Monitoring
Quality, and Increasing Sales Opportunity:
Extracting insight from the content of conversation
•
Increasing the Global Reach: Breaking the
language barrier
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