Did you know that today, 65 percent of customers prefer content in their native language? And 40 percent of customers would not order a product from a website in a language other than their own. As businesses expand into new regions, it is more important than ever that their technical manuals be translated into several languages so that they can explain their services to users in a better way to cater to a global audience.
Eliminating language barriers improves non-native buyers journey and customer satisfaction on a web platform, improving global reach. However, in the past, this took time and effort to do. Thankfully, a game-changing answer in the form of AI translations has appeared. Because of this breakthrough, translation focused on the target audience is now easier, quicker, and cheaper than ever before, as businesses do not need need to guzzle cash for hiring native speakers or linguists.
Conventional Methods of Analysis
Previously, all manual translation work had to be done by human translators who had to deal with a long set of instructions with their linguistic skills and common standards. However, there were difficulties with the technical jargon. Consider how hard it is to express complex ideas to someone who needs to learn about the topic. As mistakes were fixed and precision was maintained, this usually led to longer wait times and higher costs.
What Does the Rise of AI will Mean for the Translation Industry?
According to a study, the AI translation market, by 2030 is projected to be worth $7.5 billion, as businesses try to expand their horizons by tapping global markets and international customers. This growth directly results from the rising demand for AI-driven translation tools that are helping customers around the world.
The field of translation is already seeing the effects of artificial intelligence. Imagine a day when computers are so advanced that they can instantly convert text between any two languages they know. With the help of AI, this can now be done without any human intervention. This simplifies operations and ensures a cost-effective localisation process. Businesses no longer need as many in-house human translators as they formerly did and they can generate content in as many languages as they want without any technical education. This change may help keep expenses and increase output, making organizations more globally competitive.
Role of AI in Translation
There are several approaches that AI translation tools can use to translate text.
Machine learning
Training Machine Learning algorithms require massive amounts of data and code. This anthology has several parallel writings, which are pairs of phrases or paragraphs written in two languages but with the same meaning. Effective translation algorithms trained on the matched texts may employ the patterns they have learned to create their high-quality translations.
Statistical methods
AI translation tools use several different statistical methods. In these processes, we use statistical analysis to determine the most likely translation of a given word or phrase. We understand the requirements of the clients before deploying the translation process.
Neural networks
Machine learning algorithms called neural networks aim to mimic the operation of the human brain. Neural networks have promise for the transfer of complex information.
How Can AI Be Used to Improve Technical Manual Translations?
AI translation tools may be trained on large parallel text datasets comprising pairings of terms in several languages with the same meaning. This might be useful for identifying and translating jargon and terminology. As a result, jargon and terminology may be translated using the tools. AI tools might use this to learn how to translate technical words properly. For instance, Google Translate NMT model was trained using a massive original and translated source code database. That implies that Google Translate can easily understand medical, legal, and engineering jargon.
AI translation tools may be trained to recognize the context of all things text. This allows them to convey the meaning of statements with several interpretations more effectively. DeepL, for example is an SMT tool that has been trained on a massive corpus of source code and translated texts. With this improvement, DeepL is better able to deal with sentences that might be translated in several ways based on the context of the text it is translating.
Tools driven by artificial intelligence might be trained to translate sentences in a natural tone. This is particularly important for technical manuals, which often use specialized terminology that might be difficult to translate. Docsie is a hybrid solution to the translation issue since it draws from both statistical machine translation and neural machine translation.
Use of AI in Technical Manual Translations - Benefits and Limitations
Benefits of AI in Technical Manual Translations
1. Enhanced Productivity: Businesses may see a significant rise in productivity using modern translation solutions. These tools are always on the job, never getting weary or needing a rest, allowing for quicker and more precise translations.
2. Improved Quality Control: AI-powered translations are getting more accurate as well as lightning quick. This enhanced accuracy helps maintain the quality and integrity of technical content by lowering the potential for blunders and misinterpretations.
2. Time-Efficient Resource Allocation: Businesses may better manage their resources because of how quickly AI translation finishes tasks. This comes in handy when there is a lot of technical material to read or when time is of importance.
3. Multilingual Consistency: AI helps maintain uniformity in translations between languages, which is particularly useful when dealing with highly specialized technical jargon. Regardless of language, all readers will have the same experience reading a technical document because of this standardization.
4. Future-Ready Scalability: As businesses expand, they create more technical content, and AI can readily scale to meet these demands. This adaptability ensures that the quality will not be compromised even as the amount of translation work grows.
Reducing the impact of poor financial decisions: Using AI to translate technical texts reduces the possibility of making costly errors. Due to the precision of AI, even the most technical terms can be translated with confidence, thereby preventing costly misunderstandings. This level of precision is necessary to avoid misinterpretations that could compromise the usefulness or safety of the product.
The Limitations of AI for Technical Manual Translations
Let us discuss the constraints artificial intelligence faces while attempting to translate how-to guides. While AI has made great strides in recent years, there are still certain important constraints to keep in mind.
1. Human judgment: When it comes to choosing the right words and phrases, AI is not always as good as humans. For example, "set" might be mistakenly rendered as "juego" in Spanish. The appropriate term is "conjunto."
2. Bias: The training data is crucial to the final product's quality. AI may develop a taste for that nation's culture and language if it is fed just books from that country.
3. Security: There is a fear that putting sensitive information via an AI translator might compromise security. It is dangerous because private data might get into the wrong hands.
4. Lack of cultural context: AI may struggle to understand the cultural importance of a text, leading to inaccurate results. For example, if it translates "to pull someone's leg" (from English) to "to pull someone's hair" (from Spanish), that would make no sense in either the English or Spanish cultural contexts.
5. Potential Idiomatic Challenges: It is simple for artificial intelligence to translate words but may grapple with sentences whose meanings vary between languages. Idioms are idiomatic terms that can be challenging to comprehend literally due to their cultural connotations.
Using a hybrid system that combines machine learning with human translators is one way to overcome AI's shortcomings when translating technical manuals. Human reviewers could catch and correct any mistakes made by AI translations, which could then handle the majority of the job. Technical manuals may be translated more precisely and consistently using this integrated method without losing subtlety in the target language or cultural context.
The methods of translation can be both time consuming and expensive. They often involve hiring translators, which can significantly impact your budget. Moreover, these translators might not possess industry knowledge. It may inadvertently introduce errors during the translation process.
By automating the translation process, Docsie offers businesses an opportunity to reduce their translation costs. Making use of machine learning capabilities, Docsie ensures efficient translations, thereby saving businesses time and money.
Here Are Some Businesses That Have Implemented AI-Based Translation Of Technical Reports
Many organizations are using automation practices to replace human labor in formerly manual technical translation tasks. Some instances are as follows:
| Company | How are firms leveraging AI for technical manual translations? |
|---|---|
| Siemens | The international giant Siemens employs machine learning-based translation tools to translate its technical material into over two hundred languages. |
| Bosch | Bosch, a multinational engineering and technology company, translates its technical information into more than 150 languages using machine learning and other artificial intelligence translation tools. |
| Caterpillar | For its more than 40 countries of operation, Caterpillar utilizes machine learning translation tools to localize its technical material into the languages spoken there. |
| Microsoft | Microsoft, a global leader in modern technology, employs machine learning translation tools to localize its content into more than a hundred languages. |
| Amazon | Amazon uses machine-learning translation tools to localize content for multiple languages. |
| The internet titan Google translates its search results and other information into more than a hundred languages with the use of AI-powered localisation. | |
| Airbnb | Airbnb uses machine learning and other AI translations to localize its website and mobile app into more than 60 languages. |
| Uber | Uber uses machine learning translation tools to localize its website and mobile app into more than 60 languages. |
| Netflix | Netflix uses ML translation tools for subtitles and audio, expanding its language coverage to more than 30. |
| For more such details on AI-Based Translations, you can visit Geek Marketing, which supports small businesses by providing tailored guidance on AI tools through its blog and personalized consultations that empower effective and strategic multilingual communication. |
Artificial Intelligence's Potential Impact on the Future of Translating Technical Manuals
The future of AI may lie in specialized human-to-human translations. Machine translation tools will become better and better as AI develops. There would be a greater need for translations of technical documentation if additional languages were supported.
While this is happening, the cost of machine translation tools is decreasing. So now, companies of all sizes may localize their technical documents with the help of AI translation tools.
Machine translation tools may advance in tandem with other types of AI. They may provide more accurate interpretations than humans do because they will appreciate the subtleties of human language and cultural context. This is a great tool for businesses that need to localize their technical manuals into many tongues.
In an interview with websiteplanet, here is what Philippe Trounev, Founder & Product Manager of Docsie had to say about leveraging AI
AI is poised to revolutionize industry, with miniature AI models automating technical writing tasks, transforming the role into more of a technical editor. These powerful AI tools can enhance efficiency and content quality, potentially reducing Communication Department staff. This shift may create "writing engineers" who rely on AI for broad content generation.
In the next five years, significant changes in technical writing are expected, and your company is proactively embracing them, aiming to lead in the evolving AI-generated documentation landscape.
For More information read the full interview
Conclusion
There is promise in using AI to translate technical manuals without any technical knowledge to not just lower costs but take your company to a global scale. Companies belonging to various industries may be certain that the intricacies of human language and cultural context will be preserved in the translated versions of their technical publications when both AI and human translators are used.
Companies of all sizes would benefit greatly from using Docsie and similar artificial intelligence techniques for translating technical documentation. The advantages include accurate translation, time and money saved as well as a more direct link to an international audience.
So what are you waiting for? Visit us now!
Frequently Asked Questions
1. When compared to human translations, how accurate are AI translations?
In more technical fields, machine translations are showing signs of maturity. However, it’s possible that communication issues, such as language and cultural obstacles, will continue.
2. How much money could be saved if more people used Docsie and similar AI tools?
Some estimates put the potential cost savings for businesses using AI-driven cost-effective solutions between 40 and 60 percent.
3. Is there any human language or linguistic subtlety that a computer cannot understand?
Some subtleties and technical jargon may escape the detection of machine translation tools. Collaborative efforts with knowledgeable people may overcome these gaps.
4. How does Docsie make sure their translations are spot on?
Docsie considers the entire picture, continually updating its approaches with machine learning. Accurate translations are ensured by human review and quality assurance procedures.
5. Can specialized terminology be taught to machine translation tools?
Docsie and similar AI tools need training to understand domain-specific jargon so that they can provide relevant contextual results.
6. Where do cultural nuances and contexts fit into machine translations?
Until AI tools make significant progress in this area, human experts will be needed to handle cultural nuance and sensitivity to provide accurate and acceptable AI translations.
7. How do we get the most out of a translation team that consists of both humans and computers?
Human and machine translation work together in powerful ways. Human translators provide nuance and cultural authenticity to the text, while AI can speed up the translation process and ensure uniformity.