transforming contact centers with speech and ip jack chase, director of product management, nms rob...

Transforming Contact Centers with Speech and IP

Jack Chase, Director of Product Management , NMSRob Kassel, Senior Manager, Network Speech Products, Nuance

Agenda

The Evolution of Contact Centers Business trends Architectures

Speech Technology Update — Rob Kassel, Nuance MRCP-enabled speech

www.nmscommunications.com

Contact Center Evolution


Single anddistributed sites

Some use of IVRU and ACD

Screen pops

Some call routing via ACD

Evolution of Contact Centers: Business Trends

First Generation Second Generation Third Generation

Hardware-basedCost Center

Integration andTechnology

Solving BusinessProblems:Profit Center

Stand-alone sites

Limited PBX routing

Customer talks into phone Agent types into computer

Virtual Call Center

IVRU & ACD integration

Multi-media access: Email, fax, web

Integrated ERP/CRM

Skills-based routing


The Obvious Cost Savings Target

Agent Costs66%

Telecom Costs15%

Outsourced Calls7% Technology

12%

Source: Benchmark Portal, 2002


The Cost of Customer Interactionis Reduced with Self Service

Web

IVR

Chat Phone

Email

$0.24 $0.45

$5.00

$7.00

$5.50

$0.00

$2.00

$4.00

$6.00

$8.00

$10.00

$12.00

$14.00

$16.00

Assisted Service

Self-Service

$40

Source: Gartner Group, 2002


Evolution of Contact Centers: Technology Trends Self-service using web, ASR and TTS is

reducing the dependency on live agents; costs Web, email, and messaging are freely mixed

with phone calls in a single queue Network based contact centers are becoming a

significant phenomenon VoIP is lowering system costs at the agent and

between system components By 2007, 30% of contact center agents will be on VoIP


Circuit-Based Contact Center

ACD


CTI

IVR

PSTN

Circuit

Data

CRM

VoIP in an IP Contact Center

Site A

Site BIP-PBX

CRM

Contact Center(ACD+CTI

+IVR+Speech)

PSTN

Self-Service

Operations Center

VOIP

Circuit

Data

VOIP


Upgrading with MRCP and VXML

Site A

Site BIP-PBX

CRM

PSTN

Operations Center

Circuit

Data

VOIP

Media Server

Application Server

VXML Server

Speech Server

MRCP

RTP

SIP, CCXML

VXML


Speech Technology Update

Rob Kassel, Senior Manager, Network Speech Products, Nuance

www.nuance.com

The Need For Speech Recognition

DTMF often is used for customer self-service Numeric entry is easy… unless you are reading Spelling entry is more difficult Menus need to be enumerated, can’t be too long Deep menu structure becomes tiresome Assignment inconsistent between vendors (e.g., voicemail) How do you enter “5 ½%” or “Albuquerque”?

With speech, questions are answered naturally Caller satisfaction is higher Fewer zero-outs leads to additional cost savings

www.nuance.com

Speech Recognition Process

FeatureExtraction

FeatureExtraction

SpeechDetectorSpeechDetector

ConfidenceScoring

ConfidenceScoring

Speech

Results

Grammar

GrammarCompilerGrammarCompiler

SystemDictionary

SystemDictionary

PronunciationRules

PronunciationRules

PhonemeClassifierPhonemeClassifier Acoustic

ModelsAcousticModels

SearchSearch

www.nuance.com

Speech Recognition Challenges

Processor and memory demands Speech can be difficult to decode, even for humans

Fixed, confusable vocabularies: “B-C-D-E-G-P-T-V-Z” Ambiguous boundaries: “It’s hard to wreck a nice beach!”

Speaker variability: dialect, volume, gender, etc. Noise rejection: hands-free, mobile, telematics Out-of-vocabulary rejection & confidence measures Callers don’t always say what you might expect…

Yes or no?Yes or no?

www.nuance.com

Speech Recognition: State of the Art

Callers speak naturally in directed dialogs High accuracy, infrequent confirmation Million-word vocabularies:

stocks, proper names, street addresses Scripting to control values returned to application:

“half past three” can return “1530” or “afternoon” Open-ended responses, especially for call routing

Allows for questions like “How may I help you?” Based on statistical methods trained from examples

www.nuance.com

The Need For Text-To-Speech

Professional recordings best for fixed content Word concatenation is difficult to do well

Often used for numeric output Can sound mechanical; irritating when frequent

Large output vocabularies fairly common(e.g. city names)

Some applications defy recordings(e.g. messaging)

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TTS Text Analysis

PronunciationGeneration

PronunciationGeneration

TextNormalization

TextNormalization

Source Text

Annotated Text

SystemDictionary

SystemDictionary

PronunciationRules

PronunciationRules

ProsodyGeneration

ProsodyGeneration

“Are you there?” are + you + there + <question>$31 thirty one dollarsATM eh tee em NATO nay-tohA.M. eh em CUL8R see you later

HomographDisambiguation

HomographDisambiguation

minute = 60 seconds minute = tinyDr. Jones doctor jones Jones Dr. jones drive11210 eleven thousand two hundred ten (number)11210 one one two one oh (ZIP code)

Determine which words require emphasisInsert pauses based on phrase boundaries, lung capacityAssign duration, pitch, and volume to each phoneme

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TTS Waveform Generation

Can mimic natural speech if parameters are set by hand

In practice sounds somewhat robotic, the “drunken Swede”

Can produce a variety of voicesExtremely compact

Units can be smaller or larger than a phoneme

Database tends to be very largePreserves speaker characteristics

and speaking style of voice talent

Annotated Text

Speech

VoiceDatabase

VoiceDatabase

UnitSelection

UnitSelection

Concatenateand SmoothConcatenateand Smooth

Annotated Text

Speech

ParameterGenerationParameterGeneration

Vocal TractModel

Vocal TractModel

Parametric Concatenative

FEMALE FEMALE CHILDwww.nuance.com

Text-to-Speech: State of the Art

Naturalness of concatenative TTS is generally preferred for call center applications

…but voice talent takes direction, more expressive Custom voices to maintain brand identity Use one voice talent for both recordings and TTS

Seamlessly mix dynamic data with static prompts Apply prompt “patches” rapidly until

cost of recording session can be justified

www.nuance.com

Designing Speech Applications

Observe & interview call center agents Listen to calls, develop caller profiles

Who are they? What do they know? Where are they calling from? What are their goals? What are their priorities?

Determine business objectives & rules Define speech user interface

Call flows Prompt wording Error recovery; help and instructions Anthropomorphism and persona

www.nuance.com

MRCP and Natural Access


What is MRCP v1?

Speech servers are connected by VoIP to IVR servers Standard API for ASR and TTS Easy to reconfigure system as needs change Easy to implement redundancy

Control: MRCP/ RTSP/ TCP/ IP

Speech: G.711/ RTP/ UDP/ IP MRCP ServerMRCP Server

Speech

ServersIP

PSTN

IVR

ServersIVR

ServersSpeech

Servers


Natural Access and MRCP

Service Managers, Libraries

Driver Driver Driver IPC

Call Control

CX Boards AG Boards CG Boards PacketMediaHMP

SNMP

HMP

PCI PCI PCI IP

IVRServices

PSTNTrunking

VoIP(Fusion)

Conferencing

FaxServices

USAI(MRCP)

OAM

VideoAccess


Universal Speech Access Makes Speech Integration Easy


Current Support for Universal Speech Access

Vendor Type Universal Speech Access 1.0

Universal Speech Access 1.1

Nuance ASR MRCP Server SP5 Nuance 8.5

MRCP Server SP7 Nuance 8.5

Nuance(ScanSoft)

ASR OSMS 2.0.1

OSR 2.0

SWMS 3.1

OSR 3.0

Nuance TTS Vocalizer 3.0 Vocalizer 3.0.8

Nuance

(ScanSoft)

TTS OSMS 2.0.1

Speechify 2.0

SWMS 3.1

RealSpeak 4.0

Telisma ASR Philsoft 3.2 teliSpeech 1.0 SP4

Loquendo ASR N/A Loquendo ASR LSS 6.0


What’s Next for MRCP?

MRCP v2 draft-ietf-speechsc-mrcpv2-06, Feb 20, 2005

Adds SIP/SDP for session setup Replaces RTSP

Adds support for speaker verification Little deployment yet NMS will update USAI when deployments occur


Questions?

Contact Info:[email protected]@nuance.com

transforming contact centers with speech and ip jack chase, director of product management, nms rob...

Documents

nuance slide

contact center evolution

contact center agents

ip contact center site

network speech products

speech recognition dtmf

memory demands speech

nuance mrcpenabled speech