Post by habiba123820 on Nov 5, 2024 2:19:22 GMT -6
While some software is coded with translation in mind, translation often becomes a requirement once the software is mature. Preparing your code for translation requires paying closer attention to variables, dates, and the overall architecture of the translatable content in relation to the code. Dates, currencies, and other factors change format across regions. If they are hard-coded, they need to be recoded as dynamic entities to allow for cross-cultural flexibility. Depending on how your code is written, it can be very easy or very difficult to isolate the code from the translatable text. This will affect the next step in exporting strings, but it is perhaps the most overlooked and underestimated aspect of software translation . Every small change in the simplicity of the code relative to the text will have numerous repercussions that will affect the overall localization process. This can result in scenarios where it is challenging to preserve the integrity of the code or make it translator-friendly. Sure, you can overcome some of these challenges through analytics and segmentation strategies, but the cleaner you can export translatable content without code interference, the better (more sustainable and scalable) your software translation process will be .
Exporting software strings
Exporting strings should be a straightforward process. But it isn’t. Certain formats are preferred, while others should be avoided. Examples of go-to formats: XML, YAML, JSON. They are structured, predictable, easily parsable, and relatively easy to find patterns within the code, which reduces problems resulting from translation into different wordpress web design agency languages. Examples of formats to avoid: TXT, CSV, Mixed code. A CSV export, for example, can become a nightmare. Delimiter characters like semicolons are necessary as linguistic tools. It is virtually impossible to algorithmically distinguish between a semicolon that is used as a code break vs. a semicolon that is used as a linguistic tool. This creates hundreds of false positives that need to be checked during the QA process, as well as problems during code reimportation, etc. With mixed code, for example, we are referring to XML with JSON in it as an example, which adds complexity to the parsing and segmentation process. Coding is also a critical point:
Each of these coding frameworks will have ramifications on the localization process , including character mismatches depending on the languages covered.
Improving analysis and segmentation strategies
If you’ve followed the best practices outlined above, your parsing and segmentation strategies will be process optimizers. If you haven’t already, parsing and segmentation will become process enablers. As process optimizers, a well-tuned segmentation strategy will ensure that content is fed into your translation management system in a way that is friendly to translators and reviewers. This is where you can ensure that variables are protected, any remaining code is protected, and that text is broken down in ways that make sense for the translation process. If you haven’t done your homework, this is where things can get crazy. Either because it’s simply impossible to create enough parsing to protect the code and variables, or because it will require an insane level of effort to write enough regular expressions to make the content more translation-friendly. Either way, this is a crucial step. If you change your parsing and segmentation strategy over time, you will experience a loss of translation memory leverage, which will create extra costs and complexity in the process. It may not seem like a big deal until it blows up in your face. Let’s say, for example, that your full software is 100,000 words long and you’re translating it into 10 languages and your average cost per word is $0.15. Let’s say you’ve translated your software , but are now iterating on your analytics strategy, but this will cause a 10% loss in leverage (which might be an expected result of a small change in analytics), that’s $15,000 lost right off the bat, not to mention the extra time required and other ramifications.
Exporting software strings
Exporting strings should be a straightforward process. But it isn’t. Certain formats are preferred, while others should be avoided. Examples of go-to formats: XML, YAML, JSON. They are structured, predictable, easily parsable, and relatively easy to find patterns within the code, which reduces problems resulting from translation into different wordpress web design agency languages. Examples of formats to avoid: TXT, CSV, Mixed code. A CSV export, for example, can become a nightmare. Delimiter characters like semicolons are necessary as linguistic tools. It is virtually impossible to algorithmically distinguish between a semicolon that is used as a code break vs. a semicolon that is used as a linguistic tool. This creates hundreds of false positives that need to be checked during the QA process, as well as problems during code reimportation, etc. With mixed code, for example, we are referring to XML with JSON in it as an example, which adds complexity to the parsing and segmentation process. Coding is also a critical point:
Each of these coding frameworks will have ramifications on the localization process , including character mismatches depending on the languages covered.
Improving analysis and segmentation strategies
If you’ve followed the best practices outlined above, your parsing and segmentation strategies will be process optimizers. If you haven’t already, parsing and segmentation will become process enablers. As process optimizers, a well-tuned segmentation strategy will ensure that content is fed into your translation management system in a way that is friendly to translators and reviewers. This is where you can ensure that variables are protected, any remaining code is protected, and that text is broken down in ways that make sense for the translation process. If you haven’t done your homework, this is where things can get crazy. Either because it’s simply impossible to create enough parsing to protect the code and variables, or because it will require an insane level of effort to write enough regular expressions to make the content more translation-friendly. Either way, this is a crucial step. If you change your parsing and segmentation strategy over time, you will experience a loss of translation memory leverage, which will create extra costs and complexity in the process. It may not seem like a big deal until it blows up in your face. Let’s say, for example, that your full software is 100,000 words long and you’re translating it into 10 languages and your average cost per word is $0.15. Let’s say you’ve translated your software , but are now iterating on your analytics strategy, but this will cause a 10% loss in leverage (which might be an expected result of a small change in analytics), that’s $15,000 lost right off the bat, not to mention the extra time required and other ramifications.