NIKON PRECISION INC.

15/04/15

Can We MT Japanese?

Andy Jones Global Communications

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Poll

How many regularly MT Japanese->English?

Yes

No

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§  Nikon Precision is a photolithography equipment manufacturer with subsidiaries and offices worldwide

§  Translate avg. of 3 million characters per month (technical content)à Actual translation need is 1.5x that

§  It is difficult materialà80% of (human) translator candidates fail the test

§  Inhouse we have 7 linguists, 3 editors, 2 DTP, 1 PM + outside linguists and editors

§  Our system is a Wordbee (WB) TMS with Microsoft HUB connection for MT

The general situation

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The specific problem

Field engineers face the same communication barrier as the Dutch in 1600s!

The difference…

Tools TAUS　J

Expectations

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MT needs/Previous MT use

§  Large amount of Japanese material produced hourly –  Non-Japanese speakers cannot understand any of it –  Human translation cannot cope with volume –  Translation delays lower overall work efficiency, miscommunication

§  Rule-based MT previously used –  Easy to use, one-button translation –  “Better than nothing” –  Expensive (licenses for each user) –  Difficult to centrally manage terminology –  No longer developed

§  Various on-line MT services also used (Bing, etc.) –  Security issues

§  Need secure, low cost, customizable MT solution –  Utilizes translation memories and glossaries –  Can improve over time

-  Can understand context

-  Can learn by itself

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Sample MT system evaluation results – Usability scores

*1 = Poor, 2 = Low Medium, 3 = Medium, 4 = Good, 5 = Excellent

-  MT name kept hidden from evaluators -  System 20 got the highest overall scores

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MT system setup

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The big MT expectation game

§  Until recently, much of the history of MT is a history of broken expectations –  “Anybody can translate, so machines can do it”

–  Raised expectations are crushed

§  With great improvements in many language pairs, expectations may be nearing reality, but

§  Japanese->English is in its infancy, yet the mistaken expectation syndrome is alive and well

§  This was the case for us à big expectations suddenly emerged…even exceeding the great need…and we felt a lot of pressure i

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MT system highlights and lowlights

§  Highlights –  Tight integration of HUB and WB (leverage memory matches) –  Color coding of results (MT results in red; >90-99% in yellow)

–  Post-editing (PE) is part of workflow

§  Lowlights –  Sign-in and three clicks required •  Bing is one click!

•  Not integrated with MS Office

–  Expectations… •  In Nikon, “machine” = super accuracy, perfectly clear…

–  Cannot work offline

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What current MT is good for

§  Frequently revised (high memory match), highly consistent languageàPE only

§  Noun piles (E.g., software stringsàthousands per second, compared to HT thousands per day)

§  Gist for non-J readers who have no idea what even the subject of a text is

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What current MT is not good for

§  Intent is not clear, even just superficially (e.g., love of 曖昧/vagueness; 難しい≠“difficult”）

§  Inconsistent language, logic (MT does not ask author what s/he means, does not learn from context/immediate experience)

§  Poorly structured text (e.g., mysterious use of Excel for written content)

§  Most sentences over 7 words; handling word order and other linguistic & technical challenges

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So, can we MT Japanese?

•  For gisting? à Yes

No

The answer still depends on expected outcome

•  For use with a well-developed TM + PE à Maybe •  For reliable translations à No

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Getting to “yes”

§  Conclusion –  As a global company based in Japan, with fast-paced technical

life cycles, there is a great need for J->E translation •  We are just starting to fill this need

–  There are even greater expectations for what MT can do •  The expectation grows and seems higher after every MT

improvement…

–  To better meet expectations of both management ($) and engineers (know-how), we need to keep up with new MT developments and find the best solution

§  Our hope –  Every LSP is trying to do MT, but at least for J->E…

–  A broad cooperative effort may be the only real hope

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APPENDIX

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Nikon translation matrix

Typical Silicon valley company

Nikon

Qly

Qty

HT

Chat MT

Qly

Qty

MT

HT Email

Procedures Tech Bulletins

Sales material

Customer PPT

Often a direct correlation between quality/human translation, and quantity/MT

At Nikon, high quantity with high quality* MT + TM

+ PE

MT+PE User guides

*Mistakes are extremely expensive and not much need for social media presence

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MT system setup - Workflow

Source documents

Requestor

Matching translation from memory

Raw MT

download

FlashTrans raw output

Post-Edit

Is this information required?

No need/ Stop processing

Use the translation as-is

No

Is information sufficient?

Request post-edit to Language Services

Yes

Yes

No

Finaltranslation

RequestorDecision Process

WB Portal

WB Memory

MT (HUB Engine)

No matching memoryPost-edited data

stored in WB memory

Post-edited data used for engine training

Edited translation

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How do you rate translation quality?

Feedback from field - Initial survey result (sample 1)

-  Majority of user evaluate MT system as very useful -  Japanese users evaluated the system as less useful than English users

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Feedback from field - Initial survey result (sample 2)

How do you rate the convenience of FlashTrans?

-  Many expressed a preference for off-line access -  Again, Japanese users evaluation is lower -  Japanese uses in Japan are having problems with slow network speed at their work

sites

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Linguistic problems 1/2

§  Negation ただし、この状態はB社の装置の状態ほど悪くはありません。 However, this status is as bad as the status of the machine for the company B.

§  Katakana recognition これは清掃とウエハロット選別をすれば大丈夫という事で宜しいのでしょうか。 Are you sure you want a clean and ウエハロット selection can be avoided if this is?

§  Wrong word order XYZ上面にアイボルト(x4)を取付ける。

on top of the XYZ eye bolt (x4) install the.

Install the eye bolts (x4) on the top of the XYZ.

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Linguistic problems 2/2

§  Irregular capitalization in target segments

§  Extra spaces in target segments

§  Double-byte characters in target segments （配管を接続する。）

（ connect the tubing. ）

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Non-linguistic problems

§  Untranslated text in target segments.

§  Failure during machine translation process

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Efforts and effects for improving MT process

Efforts Effects Note Post-editing guidelines (light, medium, heavy)

Big step for overall process improvement

This is a process change. PE is faster, more effective based on light, medium, heavy project rules

Periodic retraining * Large data for specific problems * Adding TM to MT from HT

Biggest effect, though relatively small

Not programmatic (no access to phrase table, etc.) and so inefficient

Adding terms to dictionary Slight but steady

Very good on noun piles (e.g., UI strings), unique items (personal names (e.g., 山口 was Mountain Mouth and now is Yamaguchi)

Post-editing additional e-mail material

Mostly helps in the "set phrase" 決まり文句, Nikon-go (Nikon-ese) area

Initially spent most time on this but got the least impact, so stopped

Set phrases added in separate TM for 100% match Slight but steady This is follow-up after we stopped PE of

emails (above) Source document writing guidelines Negative Few follow the guidelines (no writing tool

available), and no one is happy with them Pre-edit of the source document Negative Pre-edit takes longer than HT, few SME

who have pre-edit skills Concentrate on already well-written, well-structured documents

High (memory tuning is easier, more TM)

This is a process change. Spend less time on non-standard language (emails) and more on standardized language

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Near-term Efforts

Our internal near-term efforts -  Integrate MT evaluation tools into TMS -  Develop multiple MT engines: -  SMT engine for procedural documents -  Hybrid for e-mail -  Integration of MT, TMS, and SharePoint -  Integration of FlashTrans in MS Office -  Use MT for chat -  MT offline

NIKON PRECISION INC.