2018年5月31日木曜日

高強度インターバルトレーニングを経営に応用

高強度インターバルトレーニングを経営に応用できないか?と考えています。ダラダラ働く代わりに全案件特急案件のつもりで翻訳したら週休3日を実現できるのではないかと考えています。2019年、全案件に機械翻訳活用達成後は、週休3日実現プロジェクトを開始しようと思っています。なお高強度インターバルトレーニングについては、このサイトをご覧下さい。

今日で5月も終わり。来月も頑張ろうと思っています。

2018年5月30日水曜日

SDLロードショー(大阪)に参加しました。

事務所のすぐお近くで開催されました。タワーBと書いてあったので、恐らく地下のコングレコンベンションセンターだろうと想像しました。地下に行ったら搬入作業が進行中でした。どうやらここではなさそうだと感じました(オフィスマネージャーと二人)。
やはり会場は、タワーBの10階のコンファレンスセンターでした・・・。

*前回は、確か地下だったと記憶しています。

機械翻訳に関するお話が非常に興味深かったです。是非社内で検討してみようと思います。

www.機械翻訳.com

2018年5月29日火曜日

If we only want to increase productivity, multi-lingual translation might work?

If we only want to increase productivity, we could consider multi-lingual translation. Translators who translate languages other than English will often translate multiple languages. For example, our German to Japanese translator can also translate from English. Our Japanese to German translator can, in addition to Japanese, translate from English, French, and German. If one translator can translate multiple languages, productivity will increase dramatically.

Translators who can only translate English could increase their productivity if they can add more languages to translate.

In 2018, I want to focus more on multi-lingual translation than this year and increase productivity.

This will be my last blog this year. Thank you everyone. See you in 2018!

Bye!

www.機械翻訳.com

Above is translation of an article "生産性だけを上げるなら多言語翻訳という手もあるかも?" dated December 29, 2017
Translation by Hiroko Matsuda

2018年5月28日月曜日

MT + PE will most likely be a normal business in 2019

We made an announcement that we will be implementing machine translation for all projects in 2019 (EN to JA/JA to EN). I think the timing of the announcement was just right. This is because machine translation will most likely be so ordinary that no one will pay attention to us saying that we implement machine translation in all projects.

Recently, inquiries about PE is rapidly increasing (the amount of words asked is massive! Something like 1 million words per month). Post editor training must be done as soon as possible.

To questions such as "what do you do if PE becomes mainstream?", one translator answered by saying "then I will look for another job". This is probably better considering the price. Let's see if we can survive this battle of the machine translation industry.

www.機械翻訳.com

Above is translation of an article "2019年には、MT+PEが通常業務になるだろう。" dated December 13, 2017
Translation by Hiroko Matsuda

2018年5月27日日曜日

Amazon also starting NMT!

Finally, Amazon is starting neural machine translation service as well. Unfortunately, Japanese is not included yet.

www.機械翻訳.com

Above is translation of an article "AmazonもNMTを開始!" dated November 30, 2017
Translation by Hiroko Matsuda

2018年5月25日金曜日

Judgement Day

There is a topic that has been talked about for a while. That is, a topic concerning humans losing their jobs by the emergence of MT. This is truly a Judgement day. Emergence of MT will cause the human translators to die off. We thought (around) December 31, 2017 would be the Judgement Day...

Today is that day. What happened to the translation industry? Did it collapse?

It did not. Translation companies survived. Translators are doing well. Nothing actually happened.

Manufacturers of car navigation system were having extremely hard time. Sales in car navigation system deteriorated. This is because smartphones replaced the car navigation system. On top of that, the accuracy of the smartphone car navigation system is extremely high. Did all manufacturers for car navigation system go bankrupt? No, they are here to stay. They are not busy having succeeded in the development of the next product that replaces car navigation. The product is an in-vehicle camera. Perhaps you are more familiar with the term drive recorder. The manufacturers for car navigation system won't be destroyed so easily.

The same goes for translation companies. We are not destroyed just by MT. The Judgement day is not here. However, it may not have come and may be just delayed. I will be making my next move so that the day will never come.

Of course, I already have cards in my hand.

www.機械翻訳.com


Above is translation of an article "Judgement Day (審判の日)" dated December 31, 2017
Translation by Hiroko Matsuda

2018年5月24日木曜日

弊社の翻訳者、永原、がIJET Osakaで講演を行います。

弊社の社内翻訳者の永原が、IJET Osaka (主催:JAT様)にて講演をいたします。

タイトル(日本語):機械翻訳を活用した特許翻訳業務の実際
タイトル(英語):Actuality of Patent Translation Using Machine Translation
日時:7月1日(日)、13:30~14:30
場所:グランフロント大阪、コングレコンベンションセンター

要約:近年、特許翻訳業界でも機械翻訳に大きな注目が集まっています。これからの時代、翻訳者はどのように機械翻訳と向き合い、業務に取り込んでいくべきでしょうか。弊社では、昨年度より学習型機械翻訳などの機械翻訳を導入しています。機械翻訳を使用して業務効率の改善を図る弊社の取り組みをご紹介します。

是非、皆さんお誘い合わせの上、お越し下さい。IJET OSAKAのサイトは、こちらをご覧下さい。

www.機械翻訳.com

2018年5月23日水曜日

MTPEが過半数を超えました!

MTPE(MT案件)の全案件数に対する比率です、来月は、とうとうMTPE案件が過半数を超えました!本日現在、70%ぐらいです。

来月だけの現象かもしれませんが、とりあえずいただいた案件は丁寧にやっていくしなないと思っています。

www.機械翻訳.com

One way to use MTPE

The other day, I wrote on the blog that we would step down from MTPE. There were few things I still need to mention, so I will write here.

It's not impossible for the MTPE to become faster and the price going down. However, under certain condition. If the condition is met, it can be utilized to a full potential.

It is to keep the use of NMT in translation in mind while writing the original text. That is, the text should always be written in short sentences so it is easier to machine translate.


2018年5月22日火曜日

[Harsh truth] Introduction of MTPE doesn't make translation speed any faster and it won't be any cheaper.

This is truly an unfortunate situation to write about at the end of 2017.

Introduction of MTPE does not make translation speed any faster or any cheaper. I will say this again.

Introduction of MTPE does not make translation speed any faster. Therefore, the price won't go down. 

This is the conclusion we came to after spending a year in 2017 for verification. We tried to use one project and use NMT to some how make the translation speed faster and the price cheaper. In the end, we decided to step down from MTPE.

Most likely, people in the same business as us (translation companies specializing in patent translation) have already noticed. When NMT was made available, the whole industry became excited. Each company came up with services using NMT in various ways. However, it is clear from the fact that MTPE is not offered as a product in the patent translation industry (perhaps this is good news for translators. This means that translators won't lose their jobs by NMT).

NMT cannot translate text using complex sentence structures seen in patent specifications. At first glance, you might think it is translating, but it doesn't come close to a level of "translating" for us. This is because correction is needed across the entire text.

Of course, it may be different between engine to engine, but translation output from NMT is TOEIC 800 level at most. Even if a translator at this level translates (at least regarding patent specification), we can only expect anything but a proper translation. I would be terrified. I would consider rewriting the whole text.

The biggest reason for improper translation is that translation result cannot be controlled. Even a new translator who can only get TOEIC score of 800 can unify terms when they are instructed face to face to unify "determine" being translated as 「判別する」. NMT cannot do this (Adaptive Machine Translation (AMT) can).

Therefore, there is not much of a difference in speed whether humans translate from scratch or using NMT to perform post editing. When MTPE is utilized, upon verifying within the company, it was confirmed that productivity improved to a degree of 20%. However, if we set the target of productivity improvement to 20% or so, combining the existing voice input software, software such as translation memory, and autosuccession function (?) may be enough to achieve this. There's no reason to even bother introducing NMT.

From 2018, we are considering canceling MTPE service for now. If the situation changes, we might reconsider then.

This past year, we made various efforts to incorporate NMT as one of the services. As a conclusion, we chose to step down from it. Starting from 2018, we will be switching our gears to introduce a new service.

*The above article is written only about translating patent specification. When general text is being translated, NMT is effective to an extent.
*Under a condition in which the original specification text is written with post edit in mind, using NMT might be meaningful. Therefore, it would be more meaningful if the text is written under the environment in which the applicant writes the specification and translate within a patent office.


Above is translation of an article "【残酷な事実】MTPEを導入しても翻訳速度は早くはならないし、値段も下がらない。" dated December 30, 2017
Translation by Hiroko Matsuda

2018年5月21日月曜日

Attended the Singularity Salon #26

It was about Game AI this time.

The instructor was Yoichiro Miyake (Lead AI researcher of Square Enix technology promotion department)

By the way, I don't play games at all, so I was not interested in the game part. However, I participated because I was interested in AI. The talk was extremely interesting even for people who don't know about games.

Apparently in the game industry, there is a path where a student researches about game logic > get a job at game company. I hope there will be similar path made in the translation industry as well.

The most impressionable word was "Games can no longer be created by humans alone (needs AI)". I felt that the day where the same can be said for translation would come soon.


Above is translation of an article "#26シンギュラリティサロンに参加しました。" dated December 18, 2017
Translation by Hiroko Matsuda

2018年5月19日土曜日

What is Adaptive Machine Translation (AMT)?

I'll write about the difference between Neural Machine Translation (NMT) and Adaptive Machine Translation (AMT).

In NMT, when machine translation is executed on a certain text, you cannot control the term translation. Something like this:

English (source)
.......determine............................................................................................... .....................................determines................................................................................determination................................................................................. .....................................................................determined.....................

Japanese (target)
.......判別する............................................................................................... .....................................判断する..................................................................判定する................................................................................. .....................................................................判別する....................

In this manner, there is no uniformity among target translation terms (unable to enforce uniformity).

In AMT:
English (source)
.......determine............................................................................................... .....................................determines................................................................................determination................................................................................. .....................................................................determined.....................

Japanese (target)
.......判別する............................................................................................... .....................................判別する..................................................................判別する................................................................................. .....................................................................判別する....................


When the first "determine" is translated and confirmed with 「判別する」,
the machine translation learns that term and will display the term as「判別する」in the subsequent segments.

In terms of work flow, machine translation is not executed on the entire text in the AMT. The machine translation is executed segment by segment.

Therefore, although the term "post edit" is used on NMT, when AMT is being used, it is an actual "translation" (there is no concept of post editing on the latter).

*We are currently in the process of verifying AMT. If various problems can be solved, we may implement AMT in the first half of 2018.
*Since the name includes "adaptive", I think 「適応性機械翻訳」is correct. However, considering its function and contents,  the name「学習型機械翻訳」(Learning type machine translation) is not wrong.



Above is translation of an article "Adaptive Machine Translation (AMT: 学習型機械翻訳)とは?" dated December 17, 2017
Translation by Hiroko Matsuda

2018年5月18日金曜日

70% is enough

We can get a lot of work if we are satisfied with 70%. 80% is not good. 90% is also not good. 70% is just right. In this way, work will carry on smoothly and stress free.

For example, I don't really elaborate over and over again on blog articles. There are probably many misspellings (sometimes someone will point out), but I can easily correct them. There can be no mistakes on translation jobs, so I aim for 100%. However, there are many tasks where 70% is enough.

I think it's better to focus 100% on jobs that don't allow any mistakes to be made and jobs that only require 70% concentration can be a little sloppy. It's better in terms of improving productivity if we balance our concentration on our work.


Above is translation of an article "70%で良しとする" dated December 02, 2017
Translation by Hiroko Matsuda

2018年5月17日木曜日

Books I've read: Eating style taught by doctors -The ultimate textbook-68 Medically correct ways to eat after seeing 200K patients (医者が教える食事術 最強の教科書ー20万人を診てわかった医学的に正しい食べ方68)

This book is about eating. I'm writing about this because eating right leads to better work performance.

Book: 医者が教える食事術 最強の教科書ーー20万人を診てわかった医学的に正しい食べ方68
Author: Zenji Makita
Publisher: DIAMOND, Inc.

At the beginning of the book, it mentioned the following:
1. There's no relation between calorie and obesity.
2. Dieting has little effect on your cholestrerol level.
3. Protein and amino acids destroy your liver.

Next, the following was written as a medical evidence.
  • The only cause of fat is sugar (carbohydrates). You won't gain fat from eating meat.
  • Eating fat doesn't make you fat.
  • You should exercise right after your meal to prevent your blood sugar level from increasing. If you're too full to exercise, you're eating too much.
What was interesting is that "true health cannot be gained by "temporary effort). If you are a reasonable business person, you understand that it is far more beneficial for you to focus on limiting carbohydrate intake rather than trying to maintain hard-earned muscles. Walking or going up and down the stairs for 20 minutes can be your exercise." Apparently, if you're too full to move after lunch, that means you've eaten too much. It was my first time reading about how it's actually good to exercise immediately after meals. I'll give it a try.

The book also mentioned that "if you can stabilize your blood sugar level, your daily performance will improve". This is most likely important for work productivity.

There are many methods such as changing how you work and automation by software implementation. However, I want to try changing my diet to achieve work efficiency.




2018年5月15日火曜日

マッチ率0%は廃止された

機械翻訳とか、MTPEとかありますが、あまり難しく考える必要はないと思います。マッチ率の0%が廃止されて、最低でも70%から始まると考えればそれで十分ではないでしょうか。PEに特別のテクニックは不要です。70%から翻訳を始めると考えればいいと思います。こう考えるとずいぶん気が楽になるのではないでしょうか。0%から始めるのと70%から始めるのでは大きな違いが精神的にもあると思います。いかがでしょうか。

2018年5月12日土曜日

翻訳と人工知能とについて専門家にちょっと聞いてきました

グランフロント大阪の人工知能の開発会社の方とちょっと20分ほどナレッジサロンで話しました。やはり翻訳会社は、同じようなことを考えているようでした。人工知能の利用方法に関しても知らなかったことを聞かせていただきました。機械翻訳と人工知能とを組み合わせれば面白いことができそうでした。コラボレーションは、異業種と行うべきですね。

2018年5月9日水曜日

スピードアップにつながるか?

野球でたとえるなら、一塁は、走り抜けた方が速いか、ヘッドスライディングをした方が速いかという議論と同じではないかと思います。

長らく走り抜けた方が速いと言われていましたが、ある大学教授の方が調査したところヘッドスライディングした方が速いことが判明したそうです。

一塁到達、頭からの方が速い 立命大分析、野球の定説覆す
京都新聞、2018年3月20日の記事

調査方法によっても結果は異なると思いますが。

僕は、たとえ大量のポストエディットの必要はあっても機械翻訳を使わないより機械翻訳の方が速いと考えている派閥です。みなさんはいかがでしょうか?

2018年5月7日月曜日

翻訳業界での機械翻訳、ホテル業界での民泊

翻訳業界では、機械翻訳が完全に歓迎されているわけではないだろう。今でも人が翻訳しなければならないという派閥が存在する。その人(法人)の考え方次第だからどうでもいいのだけど。

ホテル業界では、民泊が歓迎されない(という話を聞きます)。素人さんにホテル業務ができるわけがないというお立場のホテルマンがいるみたいです。

この記事を観てびっくりしました。

【速報】世界最大のホテルチェーン「マリオット」が民泊市場に参入 Airbnbに挑戦状

あのマリオット・ホテルさんが民泊に参入されるみたいです。これで民泊に対する理解が高まるかもしれません(ビジネス的に)。

機械翻訳も大手さんが大々的に活用し出すと、業界全体に広がると思います。