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INTENTO
MACHINE
TRANSLATION
INSIGHTS
Konstantin Savenkov

CEO Intento
© Intento, Inc. / May 2020
© Intento, Inc. / May 2020
ABOUT US
2
We are freshmen - 3 years in the industry
—
Tools to procure, utilise and maintain the best-fit AI. Mostly
Machine Translation.
—
Several large enterprise clients (retail, travel, tech)
—
40-70 languages each
—
Injecting MT into TMS, Customer Support, Website Translation,
Communication, Software Development, Documentation and more
—
Procurement (evaluation) → deployment → improvement.
© Intento, Inc. / May 2020
WORKING WITH MT
SAME AS WITH SOFTWARE BUT DIFFERENT
3
PROCURE
—
DEPLOY
—
MAINTAIN
train, evaluate and select
integrate with software and workflows
improve and update
© Intento, Inc. / May 2020
PROCURING MT
WHAT MAKES DIFFERENT MT DIFFERENT
4
Linguistic quality
—
Customizability
—
Tag support
FOR A GIVEN MT SYSTEM,
ALL THREE DEPEND ON
A LANGUAGE PAIR
AND DIRECTION
Intento
GENERIC STOCK MODELS
Alibaba Amazon Baidu DeepL eBay Google
GTCom IBM Kakao Microsoft Mirai ModernMT
Niutrans Naver Omniscien PROMT Rozetta SAP
SDL Sogou Systran Tencent Tilde Yandex
5© Intento, Inc. / May 2020
VERTICAL STOCK MODELS
CUSTOM TERMINOLOGY SUPPORT
AUTO DOMAIN ADAPTATION MANUAL DOMAIN ADAPTATION
Youdao
Alibaba Baidu
Cloud
Translate
Microsoft Omniscien PROMT
SAP Systran
Amazon Baidu Google IBM Microsoft Rozetta SDL Systran Yandex
Globalese Google IBM
Kantan Microsoft ModernMT
Omniscien SDL Systran
Alibaba Baidu
Cloud
Translate
Iconic
Omniscien PangeaMT Prompsit PROMT
SDL Systran Tilde Yandex
All product names, trademarks and registered trademarks are property of their respective owners. All company, product and service names used in this website are for
identification purposes only. Use of these names, trademarks and brands does not imply endorsement.
WAYS TO IMPROVE MT
© Intento, Inc. / May 2020
PROCURING MT
THINGS TO LOOK AFTER
6
Hard segments (for all MT)
—
Weak spots (for raw MT)
—
Typical segments (for PEMT)
—
One big model vs one model per
TM
—
Real-world ROI, not proxy
metrics
weak spots
hard
segments
typical
MTAGREEMENT
SENTENCE DIFFICULTY
© Intento, Inc. / May 2020
DEPLOYING MT
GETTING TO THE ROI
7
Receiving performance feedback
—
Optimizing MT vs
Optimizing workflows
—
Business side: make sure better MT yields
better ROI
© Intento, Inc. / May 2020
MAINTAINING MT
FOLLOW THE MOVING TARGET
8
Several update cycles:
- quick changes (glossaries or per-sentence training)
- regular re-training
- re-evaluation
—
Monitoring the technology updates
- terminology changes
- fluency vs fidelity trade-offs
THANKS!
ks@inten.to
9
Konstantin Savenkov, CEO

ks@inten.to

2150 Shattuck Ave

Berkeley CA 94705
INTENTO
https://inten.to

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Machine Translation Insights

  • 2. © Intento, Inc. / May 2020 ABOUT US 2 We are freshmen - 3 years in the industry — Tools to procure, utilise and maintain the best-fit AI. Mostly Machine Translation. — Several large enterprise clients (retail, travel, tech) — 40-70 languages each — Injecting MT into TMS, Customer Support, Website Translation, Communication, Software Development, Documentation and more — Procurement (evaluation) → deployment → improvement.
  • 3. © Intento, Inc. / May 2020 WORKING WITH MT SAME AS WITH SOFTWARE BUT DIFFERENT 3 PROCURE — DEPLOY — MAINTAIN train, evaluate and select integrate with software and workflows improve and update
  • 4. © Intento, Inc. / May 2020 PROCURING MT WHAT MAKES DIFFERENT MT DIFFERENT 4 Linguistic quality — Customizability — Tag support FOR A GIVEN MT SYSTEM, ALL THREE DEPEND ON A LANGUAGE PAIR AND DIRECTION
  • 5. Intento GENERIC STOCK MODELS Alibaba Amazon Baidu DeepL eBay Google GTCom IBM Kakao Microsoft Mirai ModernMT Niutrans Naver Omniscien PROMT Rozetta SAP SDL Sogou Systran Tencent Tilde Yandex 5© Intento, Inc. / May 2020 VERTICAL STOCK MODELS CUSTOM TERMINOLOGY SUPPORT AUTO DOMAIN ADAPTATION MANUAL DOMAIN ADAPTATION Youdao Alibaba Baidu Cloud Translate Microsoft Omniscien PROMT SAP Systran Amazon Baidu Google IBM Microsoft Rozetta SDL Systran Yandex Globalese Google IBM Kantan Microsoft ModernMT Omniscien SDL Systran Alibaba Baidu Cloud Translate Iconic Omniscien PangeaMT Prompsit PROMT SDL Systran Tilde Yandex All product names, trademarks and registered trademarks are property of their respective owners. All company, product and service names used in this website are for identification purposes only. Use of these names, trademarks and brands does not imply endorsement. WAYS TO IMPROVE MT
  • 6. © Intento, Inc. / May 2020 PROCURING MT THINGS TO LOOK AFTER 6 Hard segments (for all MT) — Weak spots (for raw MT) — Typical segments (for PEMT) — One big model vs one model per TM — Real-world ROI, not proxy metrics weak spots hard segments typical MTAGREEMENT SENTENCE DIFFICULTY
  • 7. © Intento, Inc. / May 2020 DEPLOYING MT GETTING TO THE ROI 7 Receiving performance feedback — Optimizing MT vs Optimizing workflows — Business side: make sure better MT yields better ROI
  • 8. © Intento, Inc. / May 2020 MAINTAINING MT FOLLOW THE MOVING TARGET 8 Several update cycles: - quick changes (glossaries or per-sentence training) - regular re-training - re-evaluation — Monitoring the technology updates - terminology changes - fluency vs fidelity trade-offs
  • 9. THANKS! ks@inten.to 9 Konstantin Savenkov, CEO ks@inten.to 2150 Shattuck Ave Berkeley CA 94705 INTENTO https://inten.to