The debate over the effectiveness of artificial intelligence (AI) vs. human capabilities is more relevant than ever. While it’s easy to fall into the trap of viewing them as rivals, the real question is how the two can work together to be more effective. A recent conversation inside Monterey Language Service highlighted this future trend, revealing the crucial role that human expertise plays in AI development.

Humans can make AI better

In copy editing, AI can analyze text for grammatical errors, and even adjust tone and style based on the context. However, as Gary pointed out, AI may handle at best 80-90% of the editing process, but the last step often requires a human touch: flexible, context-aware, and capable of grasping nuances that AI might overlook.

Mei-Ling, on the other hand, argued that the focus should be not on the limitations of AI copy editing but on celebrating its rapid development and the role humans can play in enhancing AI capabilities.

The Path Forward: Enhancing AI with Human Expertise

Mei-Ling emphasized the idea that humans can make AI even better by providing it with high-quality training data. This is an important insight: the future of AI doesn’t lie solely in its inherent capabilities but in its integration with humans.

While refining AI’s editing capabilities, we need to provide it with a variety of professional materials to cut its teeth on. There are several ways that humans can do this, and it all begins with giving AI high quality writing to train on.

But what specific steps should be taken to move forward? There are many things we can do including, but not limited to the following:

• Clearly sharing context information with AI concerning the relevant conversation or the audience
• Exposing AI to detailed examples of human conversation, including informal language, idioms, and regional dialects
• Training AI to recognize and respond to emotional cues
• Sharing cultural nuances and social norms
• Guiding AI to better understand references and humor
• To model turn-taking and back-and-forth dialogue to AI
• Helping AI understand the tone, rhythm and flow of human conversation
• Feeding high quality content to AI
• Providing feedback on how the AI’s responses come across

By combining these approaches, professional linguists can play a vital role in shaping AI. More than ever, we as human translators and interpreters have a lot of work to do, particularly in connection with individual creativity and uniqueness.

Our Previous Blogs about AI

Monterey Language Services has constantly kept an eye on AI development. Our blog series since August of 2023 has been aimed at showing how the synergy of human creativity can elevate AI performance.

Check out our previous blogs about AI:

Professional Copyediting after Content Creation: Staying ahead of the AI curve

Blue and White Porcelain: The Joy of Translation from Behind the Scenes

A Love Letter to Chinese Culture — Blue and White Porcelain Lyrics

Advice to Future Interpreters

Interpreters and Music: Translation Accuracy

Interpreters and Voices: On Human Aura

Interpreters and Voices: On Human Recording

AI Performing Music: On Human Individuality

Diversity and Richness: Interpreters and Music

Thoughts about AI: Interpreters and Music

AI and Translation

These blogs discuss AI’s capabilities, how we have worked with it and what our expectations are.

“AI is able to follow patterns to come up with solutions that others may have thought of and implemented before, but without managing to achieve such originality on their own. Is it possible for AI to progress towards greater individuality and uniqueness?” ( AI Performing Music: On Human Individuality)

“AI is capable, but then can AI interpret our tones, our feelings, our energy, our life, our passion, our emotions, and our sense of mission that professional interpreters have shared?” ( Thoughts about AI: Interpreters and Music)

 Conclusion

Rather than debating whether humans or AI did better in copy editing, the blog is intended to celebrate the collaborative efforts that can make AI development and human creativity progress together. Ultimately, it’s essential to value partnership over competition. The future of copy editing will depend on our ability to combine human expertise with artificial intelligence to create something truly remarkable.

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!

As interpreters, we are always interested in the development of interpretation technology, including the possibility of “robot” interpreters. About a year ago, we wrote about the potential of interpretation software and Microsoft’s efforts in that area. Their software is meant to analyze your speech, translate it and synthesize an audio track of your own voice speaking in the target language. (However, the software will first need to study your voice for several hours. Also, it gets around one in eight words wrong.)

So are there robot interpreters in our future? The answer is complicated. Perhaps one day, but not any time soon.

Interpretation software faces many difficulties, in each of its component stages. The first step is speech recognition, an area that has seen great improvement over the last few years. Nowadays, speech recognition figures in our daily lives – when we make a call and are asked to speak to a robot, when we are driving and asked to give commands to the stereo system, etc. Due to its wide range of applications, speech recognition is the most mature of the technologies involved, but even it still has a long way to go before it becomes truly reliable, as we are well aware from our experiences.

Next, the words spoken (and hopefully understood correctly by the system) need to be translated. While machine translation has certainly come a long way, anyone who has tried to use Google or Bing Translate on a foreign language website can testify that what comes out is not always even legible, much less an accurate translation of the source text.

Finally, the software needs to generate a spoken version of its translation through text to speech synthesis. This is possible with today’s technology, but even there many irregularities remain. Intonation, emphasis and other vocal indicators still do not carry over particularly well into artificial voice generators, creating voices that sound, well, robotic.

Beyond these basic limitations of the software, there also remain concerns about the nuances of both translation and interpretation. Questions about homonyms, about words that have multiple meanings depending on context, and of course the issue of cultural differences. There are many situations where even the most sophisticated software will be unable to guess the subtle nuances a speaker intends. A human interpreter does not just translate the words, but also the subtext and hidden meanings within them, judging not only the speaker, but also the audience.

“Reading the audience” to judge their understanding and reception of the translation is a vital skill for an interpreter. It is also one that becomes even more important in smaller, more intimate settings outside of presentations and conference interpretation. In a business meeting, at a doctor’s appointment, even in court, the message needs to be tailored based on the reactions of the listener.

Can you image a robot, as they as now, doing medical interpretation or legal interpretation?

Monterey Language Services strives to provide the highest quality of translation and interpretation services. Please feel free to contact us for a quote.

Will this software eventually replace human translators and interpreters? We think not. And here are our thoughts:

The technique behind this revolutionary translation and interpretation software is called “Deep Neural Networks,” which mimics human brain behavior. It is, however, important to note that this breakthrough took place about only two years ago. On the other hand, the first translator, Saint Jerome, has translated the Bible into Latin in the 4th century. Human translators, as a result, have been around for thousands of years. This long historical foundation is unlikely to be replaced by machines.

As amazing and groundbreaking this technology may seem, errors still exists and much more improvement is required. The software is far from perfect. Researchers pointed out that the 1 in 7 or 8 words would be incorrect. It is not error-free. However, human interpreters are able to handle error right on the spot, hence more efficient.

Technology is a double-edged sword. While science can definitely increase our quality of life, it cannot fully replace human language specialists. Only human translators can identify the subtleties in languages. Only human interpreters can detect errors. Only human linguists are able to master the art of interpretation.

Monterey Language Services strives to provide the highest quality of translation and interpretation services. Please feel free to contact us for more information.

Image source: http://en.wikipedia.org/wiki/Artificial_neural_network

A friend once asked me if I believed that my career was in danger of being outsourced to translation technology. In other words, he wondered if I felt that my profession was threatened by advances in machine translation, whereby potential clients can simply enter their text in a computer and  – voila! – an instant translation appears before them.

I told him that while technology certainly has its merits, true quality in translations can only be achieved through human attention to detail, human patience, and human passion. After all, how can a computer possibly convey the subtleties and feeling contained in a text produced by a human being, whose very essence is manifested in the words that he or she has written?

So no, I am not worried that my profession – and moreover my passion – is in danger of being made obsolete. On the contrary, I believe that every time a client of mine receives one of my translations, he or she will understand that my work, like that of an artisan whose livelihood could never be replicated in a factory, exudes the quality that can only come from the hands of a human being.

These thoughts on quality brought to you by our translator Mac Layne.

Explore the fun between human and animal communication in different languages!

Unless you were lucky enough to grow up speaking multiple languages, learning a whole new one can be an extremely difficult task. Still, people are willing to put in hundreds of dollars and hours in order to officially call themselves bilingual.

However, we aren’t the only ones capable of achieving this feat… animals are too, and it’s quite a bit simpler.

Avid Scooby-Doo fans know that our animal companions will do practically anything for a tasty snack, and that includes learning new and already-known commands in a different language. By assigning hand gestures with a command in the desired language, your dog will eventually be able to respond to the word or sentence in both languages simultaneously without the need for hand signs or body language.

If you want to see a bilingual dog in action watch this video of a man who taught his dog multiple commands in both English AND Japanese: http://www.youtube.com/watch?v=qdDMvXCeaN8

by Mei-Ling Chen

A new client commented: “I trust you will get the meaning as well as the words in all translations. It is very important.”

When customers say this to us, as Director of Translation for many years, I understand what they mean.

It is vital to get the correct meaning in translation. Even more important is to know who your author and target audience are. With this information, the experienced translator is able to make a judgment call.    

Then the translation can be written from the point of view and background of the original author. Whether from a CEO to employees; a department of communications to the general public; or a teacher to a student—the tone, style, and presentation will have to vary. This is a powerful difference that an excellent human translator can make!

With due respect to machine translation, I must say that in order to achieve the above requirements, excellent human translators are needed.  These are translators who have good sense, can analyze the text and the background, and successfully conduct research.

Sure, machine translation may be able to get a rough idea of what a passage is about and what languages are involved. But think twice whether it can boost your company’s image, or provide the quality that your company is looking for.      

If you are lucky, things might turn out right; but if a human has to edit or find bugs in the work done by machine translation, what could possibly happen?

– a waste time, resources, energy
– the need to scrap the work, and redo the entire project
– troublesome enough where you may want to smash the machine software!

This is why we believe in real, genuine devotion to quality and research when working on a translation project.