If you are bilingual and looking for a way to use it in a professional setting, chances are you are eyeing a job as a translator or an interpreter. But as you might quickly find out, it is not easy to just become an in-house translator for your dream company or a regularly used freelance translator. Like with many other jobs, clients are more comfortable hiring translators and interpreters with experience or who have proven themselves in one way or another. If you are starting out in this industry, here are some tips to keep in mind while you are making your way.

To keep an online presence. This might seem a little strange, but think about it this way: if you are looking to accept a car ride from someone, would you go with the person who has a five star rating, many customer reviews, a profile picture, and a little blurb about who they are? Or would you go with the person who has no profile picture, no rating, no reviews, and no profile picture? Obviously, you would go with the former. You would have many reservations about going with someone you have no information about. It’s the same thing with work. Having an online presence will help people who don’t even know you quickly get a feel for who you are and how you operate. Just make sure that you keep your presence online professional and active.

With a good online presence, you can also network. Networking is incredibly important for many reasons, but the most important one goes back to the previous example of a driver who you can easily read up about versus a complete stranger. When you submit your resume and cover letter to a company, especially a big company, they have to make a decision based off of the information you give them. If you don’t give them enough information, they will give the position to the person who they have a better picture of. Networking helps to get your foot in the door since you will have an opportunity to display who you are in a different, more informal setting. Networking will also help get your name into conversations making it easier for prospective clients or companies to identify you in the midst of other applicants.

You should be sure to start off small and get as much experience as you can under your belt. You would be surprised what an opportunity here or there will be able to get you in the future. Just be sure that when you do the work, you always treat it with as much care as possible. This means taking the time to ensure you have no errors, have translated everything perfectly and do not have any formatting issues. Just in case, you should have someone proofread your translation. Even if you are confident with the translation you have put out, it would be a good idea to have a pair of fresh eyes go over the work that you have done. They might have a new perspective or be able to point out some simple errors that you might have glossed over.

The last tip for this post is to set aside a specific time to do your translation. This might seem simple, but you do not want to be spending too much time or too little time on the translation. It is better to have a set time to work on the assignment than to just do it whenever you feel like it. With a schedule, you will be more committed to finishing the job, and will have clear boundaries where you can ensure you are not interrupted or distracted.

Starting out as a translator or interpreter is simultaneously exciting and frightening, but no matter where you start, you are sure to end in a good position if you persist. These tips are to provide a good starting point as well as a good base to build off of. We hope this helps anyone looking to break into the industry.

As a modern translator, there are many tools that are available now that translators in the past could only dream of having. Tools such as machine translation, spell check, macros, and online dictionaries are regularly used, leading to faster and even more accurate translations than translations of the past. However, one tool that translators might not take enough advantage of is Google. Translators might use it to generally search for articles or websites that might have information related to the subject that they are looking for, but that is only the start to what Google can help offer. In this post, we will highlight some of the most helpful tools that translators can use to enhance translations.

The first one is how to search for an exact phrase. While a dictionary can provide the exact word you want, there are often times where the word might not be used the way you think it should be, or there might be specific contexts in which it can be used or it might just be an outdated term altogether. To find out if a word or phrase you want to use can be used the way you want it to be, you can perform a Google search and put the term or phrase in quotation marks. So, for example, if you wanted to search for only the phrase raining cats and dogs, you could put it in quotation marks, “raining cats and dogs,” and then every single result will be websites that have the words in that exact order. You can also use the “verbatim” search function to search for only the word that you enter.

Next, if you want to find alternatives to words in phrases, you can use Google to search for alternatives. For example, if you wanted to search for different types of machine translation in one search, you could search like this: neural OR statistical OR rule-based machine translation. When you do that, Google will generate search results for machine translation that includes the words neural, statistical, and rule-based. This is handy if what you are searching for has numerous variations to it, but you only need a few alternatives as opposed to all of them.

On the flip side, there is a way to exclude search results from appearing. So in the case that you want all the different variations of a phrase but not something else, then you can use the minus sign to exclude the results that you don’t want. So if you want all the different kinds of machine translation, but don’t want statistical machine translation, then you can search –statistical machine translation and it will exclude all mentions of statistical machine translation. This is great if you know that you don’t want a search result to appear and are looking for other things instead.

One of the simpler tricks that does not require any special input is just comparing the amount of results that one version of a phrase generates versus another. So if you were wondering which spelling of versus is more commonly used, you could search for “vs” first and see how many hits are generated and then search “versus” and then see how many hits are generated. After comparing which one generates more, you can more confidently say that the one with more hits is the more commonly used word and therefore, safer to use in your translation.

The last trick is searching within a specific website for a specific phrase. If you wanted to look for the phrase “machine translation” on SDL’s website for example, you could search it as follows, site:sdl.com “machine translation” and then Google will generate all the instances of machine translation being mentioned on SDL’s website.

With the turn of the year, we at Monterey Language Services look forward to greeting the new year with our friends and colleagues! We can now look towards the future and remember that 2021 is a fresh start and will hold great things for all of us!

Happy New Year from everyone here at Monterey Language Services, and we wish you good health, happiness and success in the coming year!

In the last post, we spoke a bit about the different types of machine translation as well as their advantages and disadvantages. For this post, we delve a little deeper into one of the more exciting machine translation methods, Neural Machine Translation. As a quick recap, Neural Machine Translation is where deep neural networks are used to convert a sequence of words form the source language to a sequence of words to the target language. To accomplish this, Neural Machine Translations use neural networks to learn a statistical model for machine translation. Specifically, Neural Machine Translation uses an artificial neural network to predict a sequence of numbers when provided with a sequence of numbers. Simply put, words are encoded into numbers and then the numbers are input into a neural translation model and then outputs numbers which are then decoded into a translation.

How the neural network works and defines the inputted numbers to produce an output is perfected by training the network with millions of sentence pairs. So for example, if you are trying to train a Neural Machine Translation engine for English to Spanish, you would need to feed the engine a great deal of data to help tweak and refine its framework and make it more accurate. Each sentence pair that is given to the engine slightly modifies the neural network while it uses an algorithm called back-propagation. Back-propagation consists of fine-tuning the error rate that comes from the previous iteration. By properly tuning, the error rates can be reduced and the accuracy can be improved.

So what is the advantage of using Neural Machine Translation? Some of the biggest limitations of other machine translation is that they have difficulty when it comes to more complex or nuanced phrases. However, with Neural Machine Translation, it becomes much more possible to translate these kinds of phrases since the number of parameters and rules that can be given provided are much greater and therefore it is more possible to generate translations that are much more natural sounding and closer in meaning.

Neural Machine Translation is without doubt the future of Machine Translation, but there are still reasons as to why it is not widely being adopted. The biggest reason is the sheer cost and time sink that the engines require to actually become useful. As mentioned earlier, millions of sentences need to be entered into the engine for it to start to really output translations that can be considered good quality, and that means using more manpower and time. Not every company is able or willing to invest that many resources to develop a Neural Machine Translation engine, and that is perfectly understandable when weighing the cost versus the reward.

Overall, Neural Machine Translation is a complicated system, but has the most potential out of all of the Machine Translation methods. It is very possible that Neural Machine Translation will be developed to the point where it can accurately be used in a variety of situations for which it is specifically trained, but it is unknown when exactly that might happen. There have been many advancements in its development, but due to its cost and time consumption it will be quite some time before it will be able to be commonly used.

When machine translation is mentioned, the most common thing to jump to mind is Google Translate. To most people, this is the face of machine translation and any other type of machine translation is just the same as Google Translate, but inferior or superior in some shape or form. However, there are actually four different types of machine translation that exist. Each have their own advantages and disadvantages that will entice people to either use or not use them.

First, there is Statistical Machine Translation, or SMT. The best example of statistical translation is Google Translate. SMTs such as Google Translate use statistical models that draw on a large amount of bilingual text that is provided to them. Through this, they try to find statistical matches for how many times something has been translated as something. For example, if the word “apple” has been translated as “manzana” in Spanish enough times, then that becomes the SMT’s pick for the word apple. It does this for every word in the source and target language before it finally outputs a translation. SMTs can be useful for translating basic words and phrases. However, for more complex sentences, SMTs are not a good pick because they do not factor in context. This means that you can end up with some very strange sentences that do not properly reflect what is being said in the source sentence.

Next, there is the Rule-Based Machine Translation, or RBMT. As the name implies, with RBMT, the machine is translating based on the rules of grammar that it is given. It goes over the source language to analyze its grammar and then looks through the target language to see what kind of grammar rules need to be followed when translating the sentence. After it is done, it translates the sentence according to the rules that it looked up. While this might sound as if there might be fewer problems than SMTs, RBMT translations still need a great deal of proofreading to ensure that there are no problems with the text.

Third, there is the Hybrid Machine Translation, or HMT. The HMT takes elements of RBMTs and SMTs and then uses a translation memory. The addition of a translation memory makes the overall quality of the translation higher than that of SMTs and RBMTs, but there are still problems with using a HMT. For one, it still needs extensive editing, meaning that human translators will be needed to review all the translations.

The fourth, and final type of translation is Neural Machine Translation, or NMT. This type of machine translation uses neural network models that are based on the human brain to make statistical models for translation. When they work, NMTs can provide some of the most accurate translations that would need little to no editing potentially. One of NMT examples is DeepL.

Overall machine translation can be used as a tool to expedite translation, but whether it can produce clear and accurate translation for high level discussions, complex concepts, nuances and context that is still in question and requires time to advance it. This once again proves that the value of professional human translators is not replaceable just yet!

The main point of this post is to make sure that you are not trying to always do a one to one translation of the source text. Unless the specific field you are translating calls for a one to one translation, it will be much more difficult to read in the target language, and it will reflect badly on the translator. This is why some good ideas to keep in mind when translating include double checking the meanings of words in both the source and target language, thinking about the conceptual understanding of words and ideas between the source and target cultures, and avoiding idioms unless you are very sure.

For the best results when translating, it is important to always think about the context in which the source text was written and how it might be perceived if brought to the target culture. What this means is that language and culture are always very tightly intertwined with one another, so what one language might find normal, another language might find abnormal or outright offensive. For example, in the Hopi Indian language, there is no word for time, so their understanding of time is very different from most of the world where there is a defined word and definition for time. Similarly, divorce does not have its own native word in most Indian languages, and they instead use the English word “divorce,” if they ever want to get a divorce. However, divorce rates are much lower than they might be in other places in the world, due to their culture seeing marriage as a lifetime commitment. These kinds of cultural differences is why you have to do a little research when you are translating.

Similarly, in Japan, they have adapted a lot of English words into their own language and use them on a daily basis, but if an English speaking person heard these words, they might have a different idea of what they mean. For example the word “lamp” might mean a kind of light that you might find on your desk or in the room, but in Japanese, it is used almost exclusively for indicator lights. So when you translate languages that use words that appear in the target language as well, be sure to make sure that they have the same meaning in both languages.

Another thing you should be careful of is avoiding idioms altogether if you can help it. Idioms are commonplace in any language, but there will not always be an equivalent idiom in the target language. Unless the idiom is very essential to the translation, you should try to figure out a different way of phrasing it. For example, the phrase “two birds, one stone.” There may be equivalents to this in some languages, but if the target language does not have an equivalent, then you could instead say “accomplish two things with one action” or something of the sort.

While translation can be a fairly straightforward process of just taking the source words and then convert it into the target language, it can often be much more complex than that. While fields such as technical and patent translation might encourage a more one to one translation, there are some styles, phrases, and references that just won’t translate if you adapt a one to one style. That is where some creative liberties come into play where the translator tries to find replacement words or phrases that won’t always have the exact meaning of the original, but will be able to give the same nuance or elicit the same kind of reaction as the original did in the source language.

Localization is a relatively new field that people might have never heard of it or only had a vague and superficial understanding of what it means. But the truth is that the field of localization is continuously developing, and with it, there are new terms and ideas that are developing with it. One such term is hyperlocalization.

What is hyperlocalization? Hyperlocalization aims to identify, understand, and target unique micro-segments and to then localize product/service, communications, and business models in order to deliver customized solutions to meet hyper-local needs. In essence, hyperlocalization is a super focused localization process that aims to make sure that they are meeting the needs of a specific demographic by making hyperlocal content. Hyperlocal content is targeted to country-specific or locale-specific and even global-specific micro-segments within specific demographic, geographic, psychographic, behavioral, cultural or other segmentation groups. Below are some examples of hyperlocalization.

For hyperlocalization based on geographies, you might see companies changing how they localize content for a specific region or country so that it is specific to what users for that area might expect. On the other hand, hyperlocalization based on demographics focus much more on finding micro segments based on unique demographic combinations or emergent micro-trends related to age, gender, income, or education. So focusing on specific groups like millenial foodies or centennials craving brand authenticity and trying to appeal to them through targeted language and advertisements is how you might get their business.

So why is hyperlocalization so important to understand and know how to implement? Well, when localizing something, even though it is different than translation in the sense that you are tailoring the words you use to reflect the audience you are translating for, still it will be more of a shotgun approach than a targeted approach. It might sound perfectly and linguistically alright in the area you are localizing for, but that will not matter if you are not making sure you reach the group of people that would make up your core audience or consumers. Hyperlocalization achieves this by making sure that you are specifically focusing your efforts on the people who will have most interaction with the product you are localizing.

With hyperlocalization, you are getting the maximum amount of connectivity with the audience that you are trying to target with. Also, just like with localization, what you are localizing sounds natural to the target audience. The only difference is that you are making as much of the content that sound pertinent to them as possible. Hyperlocalization may not be something that you will be expected to do in the localization industry, but it is something that you should know about, so you know what is expected of you when you are asked to do it.

In the last post, we talked about the value of making relationships between Language Service Providers (LSPs) and language buyers. For the next part of this two part blog post, we will talk about recommendations on how to make these relationships. As mentioned in the previous post, creating and maintaining a strong relationship is very important when thinking about improving efficiency, workload, and overall experience for both parties. Here are some recommendations for what steps can be taken to make sure that a good relation can be established.

Let us start with what can be done from the language buyer side to improve relations. First, a language buyer should try to come up with their own requirements so that they can choose an LSP that meets their needs. Additionally, language buyers should make sure that the supplier is the right fit for the company. If they trust their supplier enough, it is possible to make the LSP a business partner and give them more privileges into the company so that they can more frequently be on the same page and know exactly what is going on.

Building a relationship with the LSP will also possibly help to foster more trust and comfort between both parties. The language buyer can also be more transparent with what they will be using services for to foster trust and understanding. After all, having a strong relationship and partnership is essential for a smooth, long-lasting business relationship.

The LSP can try to pass on as much knowledge as necessary over to the client while trying to understand their needs. However, the LSP should be careful not to overwhelm the language buyer with knowledge.  After all, the language buyer trusts that localization is the LSP’s specialty. The LSP should only try to give them relevant information that will benefit both sides. The LSP should always have the language buyer’s best interest in mind, whether it is to deliver the project timely, to convey clear meaning in translation, or to level the translation to increase the language buyer’s best image.

Overall, it is important to know that creating a strong relationship can be difficult, but it is important to show that you are committed to trying to meet all reasonable needs of each other in order to make a smoother process. There are many ways that this can be achieved, but it is important to think about what steps can be taken to move the relationship in the right direction. In the end, if you can get a strong enough relationship, then it can be possible to be comfortable being completely transparent with each other. In essence, this means that you share all the necessary information and every last detail without trying to sugar coat it. If there is some kind of issues, with a good enough relationship, there will be a high level of trust where there will be mutual cooperation to fix any problems and work on improvement plans to ensure that the same kinds of mistakes are avoided in the future.

Between language buyers and language service providers (LSPs), there is always a need to manage the relationship between one another. Simply put, without the buyer, there is no work for the LSP and without the LSP, the buyer will be at a loss too. It is therefore important to create and maintain a good relationship between one another to have an effective partnership. Here is what the LSP can do on their end to make sure that they can establish a good relationship with their buyers.

Usually, language buyers will characterize their needs and the LSP will have to do their best to capture their attention and show that they can satisfy the needs to be considered as a potential partner. In this case, the needs could be anything from time constraints, to specific languages, to translations or interpretations in specific fields, or to convey the meaning clearly. The language buyers will then look into the LSP and see if they believe that LSPs can deliver the type of service that they are looking for. If everything seems ok, they may typically take them on as a language supplier, but they will observe them over time to see if they crack or show that they are suited for their needs. The LSP will in turn do their best to try and foster a trusting relationship with the language buyer and try to make sure to meet their expectations to become a trusted supplier for frequent use and a closer partnership.

For the buyers, it starts with the fact that they have to look at themselves and figure out what exactly they are looking for and then find a LSP that can meet the most amount of requirements. They then have to continue to monitor the LSP to make sure that they are keeping up with the set expectations while also assessing whether they are the best option for the price that they are paying. They might need to understand that quality work is valuable and priceless because quality work usually requires huge efforts from the providers.

For LSPs, the efforts could be quite a few different people need to spend the weekends to go through a document before it gets to the client. Another is find issues and address problems quickly. Another is to figure out what is important and what is critical for clients in a translation or interpretation project.

We will continue to talk about the recommendations for both language buyers and LSPs, but the main point here is that a good relationship between buyers and LSPs is precious. When that happens, it’s ideal to better meet the needs of each other, to be more efficient in taking care of requests and questions from both sides, and both sides can thrive and grow together positively and effectively.

Language interpretation is commonly understood as a one to one job; for most cases, there are only two languages involved and the interpreter goes back and forth between the languages. But sometimes there are situations when multiple interpreters are needed because there are multiple target languages or that there is a rare language involved that needs to be interpreted through a third language.

For example, for a presentation in a foreign language, there might be a team of interpreters on standby, but they might not all have the same language pair. The presenter might be speaking in Japanese but only the Japanese interpreter can understand Japanese. The other interpreters however, understand English, and fortunately, the Japanese interpreter can interpret into English. Thus, the interpretation flow goes like this: Japanese presenter -> Japanese interpreter -> Other interpreters. There will obviously be a little bit of a lag between the interpreters, but in these kinds of situations, it is the only solution to ensure that all the languages are covered.

A different scenario is where there is a rare language involved and a third interpreter is needed. So for example, you might have a Triqui interpreter who can only speak Triqui and Spanish, but your client needs someone who can interpret from Triqui to English. In that case, you would need a different interpreter who can interpret from Spanish to English. Thus, the interpretation flow goes like this: Triqui -> Spanish -> English and then goes back like this: English -> Spanish -> Triqui. Relay will take a longer time, but the time is worth it because that can help interpreters perform even more accurately and completely.

There are the two common scenarios where you might need to use a relay team of interpreters. We hope this post will help you understand what language relay situations might be and how to deal with them.