In today’s globalized digital landscape, providing multilingual content on websites is crucial for reaching diverse audiences.
Traditionally, the best practice has been to prepare and embed pre-translated texts in multiple languages directly on the website, allowing users to switch languages seamlessly. However, this approach can be resource-intensive, requiring manual updates for each language version whenever the content changes. Many organizations, particularly those with limited resources, find this process cumbersome.
As an alternative, real-time translation solutions, leveraging APIs such as Google Translator or Azure Translator, offer a quick and efficient way to deliver multilingual content. By embedding a simple script on the web page, an API call can be made whenever a user switches languages.
This script sends all text content to the server for translation, reads the response, and dynamically updates the text content with the translated results. This method can be seamlessly integrated into existing web pages without altering their core structure, minimizing the need for extensive manual preparation and updates.
While real-time translation solutions offer convenience, they also present certain challenges. First, when a user switches back and forth between different languages, repeated translations on the same text can create redundancies, potentially increasing bandwidth usage and leading to higher costs. Second, the meaning of the original text might be distorted after several rounds of translation, especially if the text is repeatedly translated between different languages.
To address these issues, an optimization strategy can be implemented by designing a caching mechanism. This involves caching both the original HTML content elements and their corresponding text, as well as the translated versions. A list of HTML elements is maintained alongside a map containing lists of translated texts for each language. The index of an HTML element in the list is aligned with the index of its corresponding text in these translation lists, ensuring accurate mapping between the elements and their translations. When updating, the process involves simply replacing the text content of each HTML element with the corresponding text saved in the list for the selected language within the map. When the application is first mounted, the original text and HTML content are cached to ensure that future translations always start from the unaltered source material, avoiding any inaccuracies that might arise from translating already-translated text.
Additionally, when a user selects a new language, the script first checks if the translation for that language is already cached. If it is, the cached translations are applied immediately, reducing the need for repeated API calls and improving performance. If the translation is not cached, the script sends the original text to the translation API, stores the translated results in the cache, and then updates the web page content.
This method ensures that translations are consistent and accurate while optimizing the application’s performance by minimizing redundant API requests. By caching both the original and translated text, this approach reduces dependency on translation bandwidth, significantly decreasing the number of characters that need to be translated with each language switch. This solution can be seamlessly integrated into existing web pages without requiring any changes to their core structure, making it both effective and practical for organizations with varying needs and resources.
