Why MT Matters

Why Machine Translation Matters
Trends & Best Practices

Kirti Vashee – kirti.vashee@asiaonline.net

http://www.twitter.com/kvashee

http://kv-emptypages.blogspot.com

Copyright © 2009, Asia Online Pte Ltd

A Content Explosion Across The Globe

The Emergence of Social Media and Social Networking
as Business Drivers and Influencers

New Open Innovation & Collaboration Business Models

The Increasing Importance of Technology &
Automation

A Rising Asian Market Changing Global Enterprise
Priorities

More information was created in
2005 than in the previous 40,000
years !

Total Exabytes of Information
40,000
35,000
30,000
25,000
20,000
15,000
2009 = 800 Million Petabytes 10,000
1 PB = 1,000,000 GB 5,000
0
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
Copyright © 2009, Asia Online Pte Ltd Source: IDC Digital Universe Study, May 2010

More content will be translated than ever before
By 2012, Enterprises will be processing and managing 15
times more data than in 2007.
Each year the amount of information created in the enterprise, paper and digital combined,
grows faster than 65%. IDC
In 2012,there will be 5X as many bits created and added to the Digital Universe as in 2008.

The Digital Universe will double every
12 to 18 months


The Impact of User Generated Content
70% of Digital Universe is UGC
User Creation; Enterprise Worries
• Growing influence of social
networking and social media
• Users share opinions about Enterprise
products, services and User Generated
companies Content Touch Content
• Users trust other user opinions Consumers and
more than they trust corporate Overlap Transported,
Workers Creating,
marketing messages ~ 600 Hosted, Managed
Capturing or
Exabytes or Secured
• Word of Mouth Marketing Replicating Personal
(WOMM) is now an important Information
element of marketing strategy
• Huge impact on buying behavior ~900 Exabytes ~960 Exabytes
• Twitter as Customer Support
• Dynamic and Uncontrolled
Size of Digital Universe in 2010 – 1,200 Exabytes


As these conversations
become increasingly
independent of these
sites, falling traffic will
render them ineffective in
their current form.
Instead, the online
presence of each brand
will necessarily expand
out into the social space
to stay in touch with their
audience.

Simon Mainwaring


10X 30X
Customer
X
Exceptions Communities
Assisted Self-Service

Support Center Web Portal User Initiated Groups

Knowledge Base Community Conversations
Development/ Product
Engineering Management

Copyright © 2009, Asia Online Pte Ltd Source: Consortium for Service Innovation

Jul-Sep 07 Jul-Sep 08 Apr-Jun 09
FY08Q2 FY09Q2 FY10Q1
2%
2% 3%
5% 27%
37%

60%
93% 71%

2,895,302
Customer interactions 6,609,817
Customer interactions 8,002,883
Customer interactions

Community activity
Cisco Hewlett-Packard Microsoft Oracle
Self-service activity Symantec Yahoo! Dell Apple Intuit
Assisted – new case activity Mentor Graphics Novell VeriSign RIM
Alcatel BMC Deutsche Bank
Copyright © 2009, Asia Online Pte Ltd Introduction Source: Consortium for Service Innovation

Customer Corporate Investment
Interactions and focus
Direct Support
95%
1-3% Activity Assisted Support
Activity 10,000 @ $250/case

5-9% Self-Service Support
Activity 100,000 @ $10/exception

Community Support
90-95% of 300,000 @ $1/exception?
Activity

Indirect Support

Copyright © 2009, Asia Online Pte Ltd Source: Consortium for Service Innovation

Evolution from the G7 to the G20 World
Fast growing Asian economies and BRICI offer the fastest growing global market
opportunities and could reduce and supersede FIGS dominance in future

Top Ten Languages (by users) in the Internet
• McKinsey : 700+ Million New Asian Users will
English 478 come online over next 5 years and represent
Chinese 384 $80B+ market for infrastructure & commerce
Spanish 137 • China 770M, India 350M Users in 5 years !
Japanese 96
French 79
• Fastest growing languages on the Internet: ZH,
Portuguese 73 AR, RU, HI, ID, BrPt, MY, PH & Indic languages
German 65 • BCG: BRICI will have 1.2+ Billion Online by 2015
Arabic 50
Russia 45
• Cisco Study: Most growth in the Internet-related
Korean 37 market will occur outside of today's high income,
All the Rest 290 or "advanced," economies
Millions of Users 0 50 100 150 200 250 300 350 400 450 500
• Fastest growing digital consumer populations will
be in Asia and Brazil
42% of all Internet users in 2009 were Asian. Forecast to grow to nearly 60% by 2015
LabBrand: China is the biggest luxury market opportunity in a generation
McKinsey: China is on track to pass the United States as the home of the world’s largest R&D
workforce

 Global enterprises face a content deluge with dynamic content
coming from both internal and external sources
 High volumes of content expected to be translated increasingly
faster and faster
 Customers increasingly in control of marketing and brand messages
 A shift from corporate messaging to customer conversations and
authentic communications
More Content, Faster Turnaround Times, Lower Cost


Now, more than at any other time
in history, speed and agility are
decisive competitive advantages...
David Meerman Scott

In revolution, the best of the new is
incompatible with the best of the old. It’s
about doing things a whole new way…
Clay Shirky

 What We Translate – More Dynamic Real-Time
Content
 Why We translate – From Mandatory to Increase
and Expand Communication with Customers
 How We Translate – More Automation, MT and
Open Collaboration Models
 Highly Personalized Content to Customers when
they need it in a variety of digital forms

More Content, Continuous, Faster Turnaround, Cheaper
Project Based TEP  Continuous Streams

Low Volume, Static Content Corp Project Management
Product Cost Minimization
Product Packaging Sheets TEP Production Modes
Basic Marketing Web / User Focus on Formatting
Interface (GUI)
Basic Web Content
User Documentation

The Target Customer Localization Departments, Marketing Support
Production Model TEP (Translate > Edit > Proof)
Key Technologies Translation Memory, TMS, Email
Trados, déjà vu, Wordfast, TMS, Idiom, MS Office
Key Objectives SimShip, Customer Quality Acceptance, Formatting
Content Volatility Relatively Static, Linked to Product Updates
Integration with Customer Little if ever (CMS)
Systems


• Static Reference • Real Time Search & Find • Human Filtered
Material Mode Information
• Long Shelf Life • Information acquired as • Expert Identification
• Just In Case needed
• Trust agent based
• Mandatory and • Comprehensive & information gathering
necessary dynamic knowledge base
• Continuously flowing and
• Information flow from • Continuously Updated changing
company to consumer


Interactive
Support:
EMAIL
Knowledge Base
Data Instant Messaging
User Manuals Voice
User Generated
Support Content Blogs
Documentation

• Web 2.0 is much more interactive and dynamic
• Unstructured content in blogs, social networks is critical
• Community engagement and collaboration is key

Dynamic & Continuously Flowing Content

Human Example Words
Corporate Brochures 2,000
Corporate
Product Brochures 10,000
Products
User Interface Software Products 50,000

User Documentation Manuals / Online Help 200,000
Existing Focus
New Markets HR / Training / Reports 500,000
Enterprise Information
Communications Email / IM 10,000,000

Support / Knowledge Base Call Center / Help Desk 20,000,000+

User Generated Content Blogs / Reviews 50,000,000+
Machine

Problem: Only 0.5% of what needs to be translated today is being translated due to cost and
time constraints. TEP process slow and expensive.

Solution: Machine translation offers a potential boost that could produce “good enough”
quality for many applications.

General Purpose Customized
• Goal is to get a general • Goal is to produce near-human
understanding quality
• Generic systems that are built from • Tuned for the language style and
public domain data domain of a single customer
• Basic quality translation but intended • Built with customer data
for wide applicability
• Much higher accuracy and
• Focus = Broad but shallow translation quality
• Google, Babelfish, MSN Live and • Focus = Narrow but deep
other free sites
• Optimized for a specific customer
• Quality is only for gisting and general defined domain
understanding
• Matched to a specific purpose
• One size fits all
• Quality can be publication ready
• Loss of ownership
• Secure data, private system
• Privacy
• No volume limits
• Limits to volume
• Complete Control and Openness
• Black Box

Data Preparation
Data Cleaning Translate
Training

Combined Data Collections
Diagnostic &
Fine Tuning
Language Pair
Foundation Data

Quality
Assurance
Domain
Foundation Data

Original Translation Sources
Client Custom Domain Data

• Near-human quality translation quality is possible by combining :
• Asia Online’s Language Pair Foundation Data (516 language pairs to choose from)
• Domain Foundation Data (15 domains per language pair) with data from the client

Key Human Feedback
Correct
Targeted Corrections
Mistranslation
of Bad Learning
Syntax/Grammar
Terminology Spelling and Correct
Spelling Terminology
Punctuation
Correct
Initial System
Correct

Correct

Human Feedback can raise the raw
output to previously unseen quality levels

Linguistic Steering
Pattern Identification, Corpus Analysis,
Linguistic Problem Solver, Quality Assessment,
Linguistic Asset Development and Test & Tuning
Set Development

MT-Savvy Translators & Editors
Rapid Error Identification / Correction
Manufacture Corrective Data and Drive Early
Development of MT Engines

Less Skilled Editors to Correct Target Language
Content
Can be Monolingual, Students, Housewives
Monolingual Data Cleanup
N-gram Resolution and Preparation


 Corpus Analysis & Preparation
 Pattern Identification
 Linguistic Structural Analysis
 Linguistic Problem Solving
 Linguistic Production Process Management
 Translation & MT Engine Quality Assessment
 Rapid Quality Assessment
 Effective Use and Development of Automated Measurements
 Steering Guidance to MT Developers
 Rapid Error Detection & Correction
 Open minded translators
 Better translator workbenches and tools
 Skilled monolinguals with subject matter expertise (SME)
 Community Management
 Recruiting
 Quality Management


Initial System
put into
production

Changes are collected and Trained Internal Experts
added to initial corpus to drive begin initial clean up and
continuous retraining correction process

All users allowed to suggest Expert Users also
changes which goes through allowed to make
vetting process changes

Publication Quality Target

Post-editing effort and cost can be managed by
Quality
Post Editing Effort
improving the quality and performance of the
MT engine via corrective linguistic feedback Raw MT Quality

1 2 3 4 5 6
Engine Learning Iteration

Sales / Marketing Blogs
Product CRM
Management Biz Intelligence

TMS
Content
ECM
Management BPM

CRM
Customer Email
Support IM The Global Customer
Continuous Improvement
SMT Hybrid Engines

• Continuous Evolution Translation Systems
• Integration with content creation and content management tools
• Better standards to facilitate flow and data interchange
• Tighter integration into corporate business systems

Content Type Target Quality Process Volumes
Legal, Marketing, High Human Translation, Low
Mandatory TEP
Reference, KB Moderate Custom MT + High
Professional Post-
Editing
User Generated Moderate to Low Custom MT + Very High
Content Community Post-
Editing
Random Corporate Low - Gisting Custom Corporate High
Content MT
Random Web Low - Gisting Free MT 150 Billion Words in
Content Google Translate in
2010

Match the production process to the value, volume and quality
configuration of the content

Internal
• Product Training Materials Prioritize for Translation Process
• Manuals & Documentation
Corporate • Design & Research Develop Linguistic Profiles of Key Content
• Sales & Marketing
Content • Emails & Website

• Training Materials
Build and Leverage Linguistic Assets for
External Partner • Customer Feedback Translation Production Lines
& Customer • Customer Care & Support Different Target Quality: TEP, MT+ Post Editing,
• Customer Blogs & Forums Custom MT, Raw Corporate Baseline MT
Content • Social Network Content
Customize MT
Engine

Communicate
Translate &
Simplify & Clean
Refine MT Engine

Listen & Learn

Distribute &
Share Post-Edit and
Analyze Source
Correct

Revolutionize the Internet Revolutionize the enterprise
experience for non-English translation process with a
speakers in Asia comprehensive, continuous
learning SMT platform

Provide 1 billion+ local-language pages online
SaaS environment that allows data cleaning
using mostly translated open license content,
and preparation, develop SMT engines on
combined with compelling portal and social
demand and enable ongoing comprehensive
networking style services in Thailand,
post editing and correction to continuously
Indonesia, India, Malaysia, Philippines,
improve engines
Vietnam and China, Japan & Korea

The Consumer Market The Enterprise Market
SE Asian Languages PFIGS -CJK

Large Corporate Buyer & Translation Tools Vendor
Publisher Perspective Perspective


6,000 Finland
Key Size of circle reflects
relative amount of Denmark
Asia Japan Sweden
Europe annual R&D
5,000 Americas spending by country
Scientists & Engineers per Million People

noted. Norway
Others
USA
Canada Taiwan
Singapore
4,000
Australia
Switzerland
Russia Belgium Germany
3,000 Korea
Ireland Austria
France
Spain Netherlands
United Kingdom
2,000 Portugal
Hungary
Poland Italy Israel

South Africa
1,000 Turkey
Malaysia China
Mexico Brazil
Thailand India

0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5
R&D as a Percentage of GDP
Source: R&D Magazine (Reed), Battelle, World Bank, OECD, K4D, UNESCO, Strat-etech Consulting

English Mock-up
of Thai Wikipedia
project that was
launched in
January 2011
with funding
support by Thai
Ministry of ICT

Is already the 4th
busiest site in
Thailand and
should be the top
site by the end of
the year


• What content has the greatest value for our target
audience?
• How do we get it translated quickly, at the highest quality
possible at the lowest cost possible?
• How do we build infrastructure that enables emerging
new content to be quickly translated as needed?
• From localization projects to flowing streams of high
value customer related content


www.kv-emptypages.blogspot.com

Grazie per l’attenzione

Kirti Vashee – kirti.vashee@asiaonline.net

Follow Me on Twitter: @kvashee

Join the Automated Language Translation
Group in LinkedIn


Why MT Matters

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