In the Translation Forest, Wolfish Errors Grin with Glee. BWX AI, Set the Content Free!

Exploring AI-driven translation challenges and solutions in our linguistic journey. Join 'The AI-Translation Lab' to elevate your translation skills with BWX AI tools.

Welcome to the World of AI-Driven Translation!

A BWX AI QA a Day Keeps the Errors Away

Welcome to The AI-Translation Lab where we embark on a linguistic journey every week to explore the world of AI-driven translation. We'll delve into experiments under the umbrella of BWX's Generative AI translation features, share experiences from linguists, and reveal tips to elevate our translation skills. So, follow me to start testing.

Lab Test 4.

Translator's Challenge: Machine Translation Post-Editing Changes

One of the translators' challenges in Machine Translation Post-Editing (MTPE) is the excessive or unnecessary alterations that could potentially distort the intended meaning of the original text. This tendency to make excessive changes not only affects the quality and accuracy of the final output but also consumes additional time and resources.

Nitzke and Gros explore the challenge in translation, delving into the phenomenon known as "over-editing" in revision and post-editing processes. They argue that not all translation professionals are adequately equipped for revising translated texts and post-editing machine translations. Additionally, the authors suggest the need to include revision and post-editing skills in university curricula, emphasizing the importance of teaching methods to circumvent personal biases when suggesting alterations and to swiftly discern which text modifications are truly essential.

Conversely, under-editing presents the challenge of neglecting necessary improvements or corrections, potentially leading to errors or preserving inaccuracies from the machine-generated translation.

In the AI-Translation Lab Environment:

Source Spanish: "El curioso gato explora el misterioso jardín."

MT output in English: "The curious cat explore the garden mysterious."

Under-editing in English: "The curious cat explore the mysterious garden."

Over-editing in English: "The inquisitive feline investigates the enigmatic garden."

Balanced editing in English: "The curious cat explores the mysterious garden."

Analysis:

Source Spanish: The original sentence is grammatically correct and accurately conveys the intended meaning.

MT Output English: The machine translation has a minor error in verb form. It should be "The curious cat explores the garden mysterious."

Under-editing in English: This version corrects the verb form but still has an error. It should be "The curious cat explores the mysterious garden."

Over-editing in English: This version introduces unnecessary changes that go beyond the original meaning.

Balanced Editing in English: This version maintains the original meaning while refining the translation for naturalness and clarity. It uses the correct verb form "explores" and the more common word order "the mysterious garden."

Striking a balance between these extremes is essential for effective MTPE, ensuring that necessary changes are made without compromising the original meaning or introducing errors.

Challenges for Machine Translation: What are the poisonous species in the translation forest?

Let's picture machine translation (MT) like a forest with errors being poisonous species. To avoid a danger, translators need to know what the challenges that they will face are. In BWX, when a linguist reviews translations and makes changes to any segments in the file, the system will prompt the reviewer to categorize the change that is being made to the translations, based on a list of 6 categories.

These are the BWX error categories that the reviewer can choose from to evaluate and that the translator should have in mind when post-editing to prevent reviewer's changes:

• Preferential change (Improved fluency)
• Preferential change (Did not improve fluency)
• Fluency
• Terminology
• Incorrect translation
• Grammar

?? The way errors are categorized in BWX will have an impact on the quality score of the translator whose work the reviewer is evaluating.

What are the poisonous species in the translation forest?

• Mushrooms: The Preferential Changes Dilemmas. .Preferential Changes are like Mushrooms in the forest. You don't know if they are poisonous or not unless you are an expert. This dilemma of "keep it or throw it" needs to be efficiently solved by considering whether the change makes any difference to the fluency of the text, taking into account that unnecessary changes are poisonous for translation time management.

• Snakes: The Fluency and Syntax Strikes. Navigating language is like a serpent's path— intricate and unpredictable. Just as you must tread carefully in a forest of mushrooms, fluency requires strategic choices. Beware of syntax pitfalls. Expertise is key; mishandling changes may bite into your efficiency in translation time management.

• Nettles: The Incorrect Translation Sting. Like encountering nettles in the linguistic undergrowth, translations demand precision. Incorrect reactions, akin to an inadvertent touch, can sting. The thorny landscape of language requires finesse. Beware of mistranslation pitfalls; a misstep may leave an enduring mark on comprehension.

• Thorns: The Terminology Pains. Picture yourself in a journey through thorny thickets: precise terminology is vital in translations. Incorrect word choices, akin to encountering thorns, can be painful. Traverse the lexical landscape with care. Beware of terminology pitfalls; a wrong step may inflict lasting pains on meaning.

• Wasps: Grammar Doesn't Fly and Doesn't Lie. Maneuvering through language is like dancing with wasps—precision matters. Incorrect grammar, akin to disturbing a wasp's nest, can sting. The grammatical airspaces need care. Stay away from grammar pitfalls!

Solutions:

Addressing Quality Issues in an AAI TMS

Solution 1. A reviewer is manually classifying errors. There is the risk of subjectivity, over-editing, under-editing, and the approach is static, not bringing the corrections in an educative way to the translators and the translation project stakeholders to achieve translation skills improvement.

Solution 2. A human-led quality process. An AI tool classifies and explains modifications made during the translation process. It is a time-wise process with human-in the loop and educative benefits for translators, reviewers, clients and all stakeholders.

Conclusion:

Solution 2 is the go-to option to improve translation skills in a collaborative way during the Language Quality Assurance Process. While users can disregard the tool's recommendations, it significantly reduces the required time and effort. The information provided by the tool proves invaluable for educating reviewers, communicating with clients and stakeholders, and fueling other automation functions. By leveraging this feature, translation efficiency, and quality reach extraordinary heights, resulting in exceptional outcomes.

So, the question is:

Can BWX AI provide Efficient Categorization of Errors?

BWX Quality Professor categorizes your changes and explains their rationale as you (or your reviewers) edit translations. You can override its suggestions but they save precious time and energy and generate a ton of quality data that you can leverage to train your reviewers, provide clients and stakeholders with or just use as fuel for the BWX Autopilot.

Until next week...

• Try GEN AI Quality Module in BWX and sign-up for a free trial.
• Read this article by Gabriel Fairman to take your Translation Quality Management beyond labels and categories through AI
• Share with me your non-toxic QA experience with BWX by sending me your comments.

You will be in good company watching this video showcasing BXW AI potential: https://www.youtube.com/watch?v=VhJ4zhZ7M2o

Join me in The AI-Translation Lab as we continue to explore and address the intricacies of translation and how AI tools can elevate translators' skills in our linguistic journey.

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