How Do You Say Rogue One in Russian?

Image by JD Hancock on Flickr

Disclaimer: This post examines Rogue One: A Star Wars Story as a case study of cultural adaptation in film translation. I was not involved in translating any materials for the film.

By now, many people will have seen and enjoyed a Star Wars spin-off movie Rogue One. One of the things that occurred to me after watching it was the challenge of translating the word “rogue.”

Without spoiling too much of the plot, Rogue One is the self-proclaimed name of a stolen spacecraft that goes on an unauthorized, desperate mission. Unabridged defines “rogue” as follows:

10. (of an animal) having an abnormally savage or unpredictable disposition, as a rogue elephant.
11. no longer obedient, belonging, or accepted and hence not controllable or answerable; renegade: a rogue cop; a rogue union local.

In the film, taking this daredevil initiative against all odds is portrayed as a courageous, if foolhardy, endeavor. In other words, “rogue” needed to express these shades of meaning:

  • stealthy
  • unauthorized
  • going out on your own
  • possibly illegal

What Russian words would make a suitable spaceship name yet convey this positive sense of “rogue”? Here are some options I weighed before looking up the actual approved translation. Each of them successfully represents some aspects of “rogue” but may fail to represent others.

Otchayanny (отчаянный) – Desperate/Daredevil

Image by Martin Wessely on Unsplash

First of all, I decided to look at some typical names for vessels. As there have been comparatively few spacecraft, I included sea vessels in my search. As it turns out, Russian destroyers have traditionally been named with adjectives.

I thought the Russian word otchayanny (“desperate, daredevil”) conveyed the sense of having the immense pluck to go on a dangerous, clandestine mission. At the same time, отчаянный evokes despair and a sense of a doomed, last-resort effort, which may unintentionally send a negative message. The English word “rogue” also has negative connotations in some contexts, so this may not be a game-stopper.

Otvazhny (отважный) — Courageous

Otvazhny was another possible candidate. This adjective has the advantage of communicating a strong, positive message — bravery and willingness to take risks. However, it does not convey the illicit shades of “rogue” and makes the mission sound much less controversial. Several other adjectives shared these traits, e.g. besstrashny, “fearless.”

Partizan (партизан) — Partisan/Guerilla

Image by Matt McGillivray on Flickr

I had also considered the noun partizan (“guerilla fighter, underground resistance member, wartime partisan“) for the name. As partisans have often been a sort of guerilla militias organized to sabotage enemy operation, this aligned nicely with the plot of the film and conveyed the sense of an unauthorized, undercover mission. At the same time, partizan is also used colloquially to jokingly refer to someone who undertakes things with no proper planning and with dubious outcomes.

So what was the official translation?

The official Russian release, as I eventually learned, opted for izgoy (изгой, outcast). Just as the proposed translations above, this variant captures some important aspects of “rogue” — being shunned by your community and denied its support, possibly for something unorthodox you suggested. At the same time, izgoy only captures the expulsion aspect and does not convey the sense of taking matters into your own hands against all odds and despite the lack of official authorization.

What translation do you think is closest to the English?

While I was not involved in the translation of this film, I have worked on audiovisual projects ranging from subtitling to interpreting at film premieres. Take a look some of the films I have translated on my Translation page.

Live and Learn: Post-Mortem of #ATA57

San Francisco Skyline seen from Dolores Park // Image by Maria Guzenko

This year I went to my second American Translators Association (ATA) conference as a full-time independent translator (there was also that time in 2011). Since my conference review from last year mentioned some things I could improve, I would like to use this post as a follow-up to hold myself accountable for my progress in various areas of professional development.

Division Activities

“Home Base” Division

One of the goals I set for myself last year was participating in events hosted by the divisions of the ATA I am a member of. Since I attended the Slavic Languages Division (SLD) meeting last year, this year that division served as my “home base” — I recognized several people at division events and made sure I participated in at least some of their activities.

Newcomers Lunch

These activities included the division meeting, like last year, and the SLD newcomers lunch. I had not even realized the latter was in the works, but I am glad I participated. For the newcomers lunch, new translators and division veterans headed down to a restaurant in the vicinity of the conference venue for an informal meal and conversation. I have found it to be a viable and cost-effective alternative to the division dinner, which I did not attend due to cost and conflicts with other night-time networking opportunities.

Branching Out

Unfortunately, I was not able to attend the Medical Division meeting as I had hoped because it was scheduled at the time as the SLD meeting. However, I did attend the meeting of the Literary Division for the first time, which was very enlightening. Although I had not done fiction translations for publication to date, it was great to hear colleagues’ ideas on getting into the field.

Meeting Colleagues

Another goal I set last year was to arrange meetings with colleagues ahead of time. I can say that I made modest progress in that domain. Before arriving at the conference, I went through the list of attendees in the conference app and marked the names of the people I might be interested in meeting.

Planned Meetings

In the end, I only officially set up a meeting with Alaina Brantner, a project manager and translator whom I had met at last year’s conference. However, going through the list of names proved useful as I ended up spotting colleagues in the hallway whose name I had noticed on the list.

Virtual Colleagues

In addition, I mustered the courage to approach Marion Rhodes, whom I follow on social media and tell her I enjoyed her posts. My challenge for next year remains to introduce myself (in real life, as they say) to additional esteemed colleagues I follow on social media.

Chance Encounters

On the positive side, chance encounters in the exhibition hall proved surprisingly enlightening. For instance, I exchanged business cards with fellow translator Sarah Hotung and then noticed hers said she had attended a school I was curious about. So I set up another brief meeting with her to talk about her experience with that school.


Ice rink by the Ferry Terminal Building // Image by Maria Guzenko

I feel like this time I was not as involved with structured networking as last year, for instance at the welcome reception or job fair. Other activities, such as brainstorm networking and #TweetUP remain on my to-do list for the future.

External Events

At the same time, I am happy with the informal networking that happened outside the planned events. The annual Kent State University lunch gave me a chance to catch up with fellow alumni and meet recent graduates of my translation program. Moreover, I had a productive and enjoyable time at the networking dinners organized by external organizations — Transperfect and Wordfast. By now, I was more comfortable talking to other professionals in the industry and was genuinely interested to hear their insights and perspectives.

Impromptu Networking

Some of the best conversations I had came about spontaneously. On the last night of the conference, two other translators from the Slavic division — Alyssa Yorgan-Nosova and Ekaterina Howard — and I were looking for a place to get dinner. We decided on a Chinese restaurant we looked up online, which ended up having amazing, reasonably priced food, and had a great time sharing stories about from our professional and personal lives.
I would love to hear from other attendees, especially ones who had set goals for themselves at previous conferences. What did you or did you not achieve? Were there any unexpected positive experiences?

Machine Translation Unlikely Substitute For Human Decision-Making

Image: Unsplash

Are we finally on the brink of machine translation catching up to human translators? Recent coverage of neural machine translation (NMT) seems to suggest so. Beyond the justified skepticism about what machine translation (MT) can achieve, this attitude overlooks the choices we make in translations.

As Good As Human Translation?

The recently developed Google Neural Machine Translation has been hailed as producing superior results to (currently available) phrase-based machine translation and even approaching human translation quality. The translation company Systran has announced its own version of neural machine translation. However, as Kirti Vashee points out, Google’s method of scoring translations ends up overstating the actual improvements in the output. Experts interviewed by Slator also questioned the methodology used to assess the progress.

Many of the claims centered on whether neural machine translation was “nearly indistinguishable from human translation.” In fact, the basis for scoring Google’s translation was comparing machine-translated excerpts from a variety of texts with their human-translated counterparts. However, there is little discussion of what makes a good human translation or a good translation overall.

Automation and Decision-Making

At this stage of technological development, we would likely not brand a company with a computer-designed logo or publish computer-written fiction without having a human direct or edit the output (advances in computer-generated journalism notwithstanding). It is thought that when technology automates some of the menial jobs, humans will still be needed for the more creative tasks.

In my view, what makes these jobs hard to automate — at the current state of artificial intelligence — is the decision-making process involved. While a car being assembled has exact specifications of the final product, a logo or a marketing text is ostensibly a more open-ended task, where the final product isn’t obvious at the beginning of the process.

A “Perfect” Translation?

Image: Unsplash

Yet translation is somehow treated differently. It is tempting to discount the infinite-possibility decision-making process involved — after all, the source text has already been written and it would seems that all decisions have been made. All that’s left to do is recast them in the other language. Indeed, Google limits its criteria of a “perfect” translation to “the meaning of the translation [being] completely consistent with the source, and the grammar [being] correct.”

This approach implies there is one correct translation, and the task of both human and machine translators is to arrive at it. However, there is arguably more than one acceptable output, depending on the purpose and target audience. A functional approach to translation postulates that

[It] is not the source text as such, or its effects on the source-text recipient, or the function assigned to it by the author, that determines the translation process, … but the prospective function or skopos of the target text as determined by the initiator’s, i.e. client’s, needs.

For example, the same public health brochure may justifiably have to be translated differently for a Russian-speaking population in the US as compared to a Russian-based target audience. The first group is more likely to be familiar with US-specific healthcare concepts, such as “co-pay” or “nurse practitioner,” whereas the second group will need an explanation or adaptation. The same is true for cases when an accurate translation evokes negative connotations.

Making the Choice

We see that most utterances in the source language allow for several adequate translations. Does that mean that machine translation that produces any of these potentially acceptable translations at random has fulfilled its purpose?

While I am not qualified to comment on the programming behind neural machine translation, according to published research, the probability of a certain translation occurring in the set the NMT system was “trained on” is taken into account when making the final choice. In other words, in the best case scenario, NMT will pick a reasonable, grammatically correct, most likely translation based on its training dataset.

For many text types, this may be quite satisfactory. But is the most likely or the most common choice always the most appropriate one? Even after machine translation has surmounted the challenges of grammar and syntax, which is no small feat, I believe many clients and authors who care about their message will still rely on the judgment of the human translator — if only to make sure the machine made the right choice.

Shortcomings of (Untrained) Native Translators

notebook and coffee on a deskShould translations be done exclusively by native speakers of the target (“into”) language? This question has recently come up in several publications. The language industry and training programs in the US predominantly answer in the affirmative. I have speculated about some possible reasons for this attitude.

A recent article in the American Translators Association (ATA) Chronicle reported that in a blind evaluation of translations by native and non-native speakers, there seemed to be no clear correlation between the translator’s native language and the evaluation their translation received. In addition, The Conversation recently ran a thought-provoking piece on why native speakers of English unexpectedly stumble in international Anglophone business environments.

While native speakers undoubtedly have an edge when translating into their first language, merely being a native speaker is far from sufficient to qualify a person to be a professional translator — or writer. Listed below are a few shortcomings untrained native speakers may exhibit when it comes to their native language.

Ignorance of Other Regional Varieties

globeFirst, native speakers may be attuned to the variety of language as spoken in their home region and ignorant or dismissive of other varieties of the same language. This is especially true of languages spoken in diverse locales, such as Spanish, English, or Arabic; however, I’ve encountered it with the usually uniform Russian.

I came across the expression bolshaya komnata (literally “big room”) that was given in a textbook as the equivalent of the English “living room,” and I thought, surely, this must be a mistake. All my life I had heard zal or gostinaya for “living room.” It was not until I spoke with a colleague of mine from St. Petersburg that I realized this was a legitimate regional variant.

In other words, native speakers who have not been specifically trained in distinct varieties of their language will default to their local dialect, whether or not that is appropriate for that target audience. As the Conversation article pointed out,

The inability of the travelling native English speaker to refrain from homeland idiosyncrasies, subtextual dexterity and cultural in-jokes has been found to result in resentment and suspicion.

What this means: native speakers may correct or mark as wrong expressions from dialects they are unfamiliar with.

What to do: make sure your translator is aware of the target region for the text and is familiar with the language as used in that region.

Poor Knowledge of Language Conventions

woman writingVery often, the only yardstick against which a native speaker without language training can measure a passage is whether it is something they would say. However, this same native speaker may not always know or remember the conventions of their language.

One example is the usage of “whom” vs “who” (basically, “whom” cannot be the subject of a sentence/clause). A former ESL teacher insisted the difference didn’t matter because “no one says ‘whom,’ anyway.” This confusion can be seen when countless publications from The Guardian to The Atlantic misuse “whom” in a subject position.

What this means: if a native speaker is only basing their opinions on what they say in everyday conversations, they may be unable to author or edit a passage that uses an unfamiliar turn of phrase.

What to do: contract work to professionals with extensive training and experience in the genre and subject matter of your text — and, yes, that means a solid grasp of formal writing, if needed.

Hypercorrection/Language Myths

booksThe opposite extreme untrained native speakers tend to go to is insisting on corrections based on outdated, misguided, or preferential “rules.”

The dreaded split infinitive is a notorious example in English. People may also insist that “farther” should be used for distance, and “further,” for everything else (follow the link to hear how this distinction emerged). Finally, in their desire to avoid what they’ve been taught is an error, speakers will slip into hypercorrection, saying things like “between you and I.”

What this means: an untrained native speaker may correct perfectly acceptable writing because that speaker has been taught that a certain turn of phrase is verboten — or because they confuse it with a different use case.

What to do: make sure the person who does writing or translation for you does not only rely on what they once learned in high school or read on the Internet — they need to have solid reference materials and research skills in order to back up any proposed change.

While it may sound counterintuitive, simply being a native speaker does not guarantee a high standard of writing. I have touched upon some of the areas untrained native speakers may be weak in, but there are many others, such as domain-specific language, consistency, and so on and so forth. Now, a native speaker with specialized training is a force to reckon with — but perhaps so is a trained second-language speaker? I would love to hear your perspective in the comments.

Guilty By Association: When Idiomatic Translation Hurts Your Message


One of the benchmarks of a good translation is whether it sounds “natural” or “flows.” In other words, you want the translation to use language that is frequently used by the target audience and resonates with them.

An important exception to this rule is when the “natural,” idiomatic expression has negative connotations in that language. Such cases may warrant a departure from the choices made in the original text. Below are a couple of examples that illustrate this point for Russian.


Woman on the subway

“Single” is defined as “[u]nmarried or not involved in a stable sexual relationship.” This word may be used in screening questions about marital status or in target market demographic breakdown.

What are some common Russian equivalents? In official papers, you will see nezhenatyi (неженатый, unmarried) for men and nezamuzhnyaya (незамужняя, unmarried) for women. This may not always work for your purposes — these terms are gender-specific and may include unmarried people in relationships, who are, by definition, not single.

When discussing single parenthood, the customary Russian term is materi-odinochki (матери-одиночки, literally “lone mothers”). This does not sound very positive and probably shouldn’t be used by a business to describe its potential customers.

As a result, you may want to be creative with the translation. If you need a gender-neutral, non-negative way of saying “not in a relationship,” you may choose something like ne sostoyashii v otnosheniyah (не состоящий в отношениях, “not in a relationship”). It may sound less usual, but it also doesn’t come with the “baggage” of the native terms.

“Having a Drink”

Two bottles of beer

Doesn’t having a drink with your friends sound fabulous and almost innocent? However, finding an adequate equivalent in Russian may be surprisingly challenging. It appears that, despite (or due to?) high rates of alcohol consumption, the Russian language attaches a social stigma to drinking.

Vypivat’ (выпивать, “to occasionally have a(n alcoholic) drink”) is typically used when talking about vices, as in “он выпивает” (on vypivaet, “he’s a drinker”). That’s probably not the image you want to project when talking about having a drink with your friends.

Another variant potreblyat’ alkogol/spirtnye napitki (потреблять алкоголь/спиртные напитки, “to consume alcohol/alcoholic drinks”) sounds like a part of a health study on alcohol consumption. This is not ideal if you want to present drinking as a fun and laid-back activity.

That means that if your materials contain references to drinking, you may need to forgo the usual, “natural-sounding” translation in favor of more creative, positive wordings. If you are talking about a specific kind of drink, for example wine, you may choose to say vypit’ bokal vina (выпить бокал вина, “to have a glass of wine”), which sounds classy and non-judgmental.

In other words, you don’t always want to stop at the popular, commonly-accepted translation if it does not represent your brand message and the desired associations. These cases justify and even require a departure from the choices made in English in order to ensure the desired impact in translation.

Are Your Corporate Materials Localization-Ready?

man writing notes

US-headquartered corporations will often want to expand their operations overseas. At the same time, few of them internationalize their corporate communications and training materials. In other words, the original content was authored with the US in mind, and when the company decides to publish this content abroad — to localize it for other markets — it turns out that parts of it are inappropriate for the overseas audience.

References To US Resources

woman on the phoneOne common thing authors seem to overlook when sending documents for translation is content that is only applicable in the US. For example, the company might promote its toll-free 800 number, although it may be unreachable outside North America. The solution here would be to list a local toll-free number in the target market or, if you don’t have one, to list your normal US number with the country and area code included.

Another example is a company equal-opportunity employment policy that lists all unacceptable grounds for discrimination and end the list with “and other characteristics protected by law.” This may be misleading in a country where protected characteristics differ from those under US law. What the company can do is list any characteristics it does not discriminate on and replace the reference to the US-specific equal opportunity employment regulations with “applicable law.”

Presumed Values

diverse group of peopleImplicit assumptions also pose a challenge for localization. For instance, you may include in your employee training materials names like Zhao, Ben, Tyra, and Carmen. The implicit assumption there is that the company is diverse and various populations are represented in the workforce. However, leaving the names as is may only confuse your overseas audience, who will not have the same association with the names and may be left wondering why bizarre names are used in local training materials.

You may want to come up with a localization strategy and include it in the translation brief for your translation provider. You may choose to give them license to use “typical” names from the target country to make the training read more natural for the locale. If you wish to preserve diversity, you may want to instruct them to include names typical for various groups in the target country. Finally, if you choose to leave the names as is, make sure they do not sound comical or obscene in the target language.

In some cases, values you perceive as worth implementing in your culture may be met with suspicion and even hostility in the new market. For example, a company may encourage reporting violations to superiors. This requirement breaks an unspoken taboo on “snitching” for the former USSR, where people could be imprisoned or worse based on reports submitted by jealous neighbors. If you want to encourage reporting misconduct, you may need to include an explanation of why this is beneficial for all employees and why this is morally acceptable and even commendable. These values may be second-nature to the initial audience, but not to the target audience.

These are some salient points I have encountered working on corporate communications thus far. I would love to hear from people working in other language combinations about their experience. Can you think of any examples of successful internationalization?

3 Checks For Your Automated Translation (If You Can’t Help Using It)


Bad automated translations have become infamous on the Internet. Business are advised against using “raw” machine translation. Finally, you might have read about an embarrassing mistranslation that made it onto the official site of a Spanish food festival.

To grossly simplify the mechanism, machine translation is normally a combination of substitution rules and large corpora (collections) of texts in the two languages that help the software “decide” what each original string corresponds to in translation. This technology can yield good results when we use domain-specific corpora, controlled authoring, and human post-editing for high-visibility or high-stakes content.

I understand why these best practices need to be followed, you might say, but I am no Fortune 500 company — I cannot afford to hire a human translator or post-editor. I only need to translate this street sign or ask my Italian in-laws what they want for dinner. While augmenting machine translation with the practices mentioned above is still highly recommended for any business/official communication, I would like to share some techniques to check your automated translation when you cannot use other options.

Use Longer Phrases

One of the challenges for machine translation is ambiguity in language — one word can mean different things in different contexts. The way to help the software overcome this is to give it more context. Consider the following example from this BBC article:

English The little car you can drive in France without a licence Losing one’s driving licence in the UK is a serious matter – expensive and, to say the least, very inconvenient.
Google Translation (Russian) Маленькая машина можно ехать во Франции без лицензии Потеря свое водительское удостоверение в Великобритании серьезный вопрос – дорого и, по меньшей мере, очень неудобно.
Bing Translation (Russian) Маленький автомобиль вы можете управлять во Франции без лицензии Теряя водительские права в Великобритании это серьезный вопрос – дорого и, мягко говоря, очень неудобно.

vintage carPutting aside grammatical incongruities for a moment, we see that in the first instance, both Google and Bing translated “licence” as litsenziya (лицензия), which is a business or medical license in Russian, but not the document that lets you drive a car. In the second sentence, however, the combination “driving licence” has swayed the result in the correct direction of voditelskiye prava or voditelskoye udostovereniye (both meaning “driver’s license”).


In the example above, both Google and Bing gave similar results. However, that is not always the case. Take this sentence from a post on the Snob website.

Russian С полгода назад ко мне на прием пришла женщина и попросила совета.
Google Translation (English) About half a year ago I was at the reception woman came and asked for advice.
Bing Translation (English) With half a year ago to me came a woman and asked the Council.

professional womanThe Russian actually says “About half a year ago a woman came to see me [at my office] and asked for advice.” We see that Google produced accurate translations for the timeframe and asking for advice, but it did not convey that this interaction happened at a counseling appointment. Bing, on the other hand, did convey that the woman had come to see the author, but picked the incorrect variant for sovet (advice vs council).

In other words, if you are machine translating something for comprehension and not for further publication, try running the same sentence or text through more than one automated translation engine to cross-check the output and detect any common threads or discrepancies.

Round-Trip It

Finally, if you are translating from a language you know and absolutely cannot use a human translator to do or check the work, don’t just stop at the first automated translation you get. Take that output and machine translate it back. See if the output makes any sense.

For instance, try round-tripping the sentence “A land where dinosaurs once roamed, this prehistoric evolutionary cauldron is a playground for naturalists” from a CNN travel article. You may want to use a different automated translation engine than the one you used to do the first translation. I have seen some comical results with this sentence.

I would especially like to hear from people outside the language industry — do you use machine translation in your work? What made you chose this method over others? How do you make sure the translation is meeting your expectations?

How Bad Is Translation Expansion in Russian (And How To Curb It)

hot air balloons
Image: StockSnap

We say that a text “expands” if its translation takes up more space on the page or screen than the original content. Expansion causes problems for layouts created without localization in mind as the translation will be truncated to the point of being unintelligible, or the design will need to be re-worked to accommodate the expanded text. Consequently, developers are encouraged to leave enough space in the user interface to accommodate expansion.

Russian is supposed to expand greatly and wreak havoc on your user interface. But does it really expand that much? Let’s look at a few numbers first.

Continue reading How Bad Is Translation Expansion in Russian (And How To Curb It)

Lessons Learned from ATA 56th Annual Conference

Wynwood Walls in Miami
Wynwood Walls in Miami // Image mine

This year I attended the American Translators Association (ATA) annual conference after a three-year gap. This post is a quasi-debriefing of what I thought went well this time and what I need to concentrate on in the following years. By its nature, the list will be specific to me and may not reflect everyone’s priorities and experience. I am sharing it here for any colleagues who may find it useful. I will be happy to hear your perspective and compare notes.
Some background is in order. The first time I went to ATA was in 2011, when I was a graduate student in translation. I couchsurfed and had to commute to the venue and missed a few sessions as a result. I was also unaware of the external networking opportunities, which I will cover in this post. This time, I feel I took better advantage of the conference for the following reasons.

Ideas That Worked

Stay Close To The Conference Venue

This was a pivotal decision that enabled me to seize the other opportunities I am going to describe in this post. The hotel where the conference was held charged a hefty sum — especially for a single room — which I found too steep. However, I was able to stay close by without the expense at an airbnb 10 minutes away from the hotel. While it did not provide the same level of convenience and privacy as a hotel room would have, it offered a more affordable rate without compromising proximity to conference events and informal networking opportunities.

Continue reading Lessons Learned from ATA 56th Annual Conference

Coding Approaches That Foil Russian Localization

pieces of a jiggsaw puzzle

Making the next ubiquitous app is the holy grail of many tech startups. Yet localization is often an afterthought for an initially English-only application. So when you are ready to take your app to other markets, certain assumptions that were made for English no longer work for the localized app. Here are three approaches that will make your app less functional and user-friendly in Russian.

The Lego Approach

Lego blocksConcatenation is a coding technique that strings different sequences of characters together to form a sentence. For example, a newsfeed update may be coded as “[username] posted [number] pictures,” where the username and number are pulled in from a database and the rest of the phrase is static. This sounds like an efficient approach that helps you recycle the building blocks of language instead of having multiple variations of the same string — in English.

However, in Russian as an example, “added” will be different depending on whether the subject (so, your user) is feminine, masculine, neuter, or plural. “Pictures” will be different depending on the number that precedes it, much like in English, except that the form for 2-4 is different from the form for 5-10. Why such complexity, you may ask? Some theories of language postulate that redundancy, or repeating parts of the message, helps the listener or language learner catch the message if they missed one part of it.

We may not like having to alter our perfectly functional English code to accommodate “less efficient” languages, but not doing so will result in a foreign equivalent of broken English. To illustrate this, let’s look at an analytic language without verb tenses or plural forms for nouns, like Mandarin. If a developer coming from the perspective of that language had coded something like “[username] like this post,” where “like” does not change in terms of person or tense, this could potentially result in ungrammatical sentences like “Joe like this post.” While this is still understandable, it does not have the same feel as the original copy.

The Unisex Approach

old letterA related pitfall to avoid is ignoring the concept of grammatical gender. Even basic boilerplate language like the greeting “Dear” in an email salutation will need to be different depending on whether the recipient is male or female. While this means more things to keep track of in your database, this will result in the same standard of writing as was applied to the communication in English.

As a side note, the lack of an established gender-neutral pronoun does present a challenge in Russian. In any case, you should be able to track and display the user’s preferred pronouns and adjective gender.

The Buddy Approach

dog with a ballA final difference to keep in mind is the US developers’ propensity for informal, approachable language. This is evidenced by humorous error messages along the lines of “Oops, something went wrong” or status messages saying “Sit tight.” This is unusual for Russian, where the audience expects a more straightforward and slightly drier style.

For example, an application is unlikely to add “please” or “thank you” to the message it displays. As a result, the Microsoft style guide for Russian recommends translating “No line, thank you” as “Без линии” (Bez linii, literally “No line”) to ensure proper register. While some of these stylistic quirks of English authoring may be neutralized in translation with the help of a style guide, it is best to internationalize your code from the outset to avoid linguistic — as well as technical — obstacles to successful localization.

Understandably, even with the best practices in mind, developers may miss an aspect that makes localization in a specific language difficult. That is why it is so important to consult your localization provider at various stages of software development. This way, you will be able to make your app a little more international — in the next version, if not the current one.