Studying our translation agency website statistics, a whole "cluster of requests" related to the analysis and processing of text attracts attention. Our website has a module that is designed to remove numbers and letters of Russian and English from text. This is used by our managers when it is necessary to calculate the cost of translation (and therefore the volume of text) of documents such as a bilingual contract or technical instructions, a price list or a balance sheet or a report in which there are more numbers than words.
Removing Cyrillic from text may be necessary for several reasons:
Calculating the cost of translation
One of the main reasons why our managers use this module is the need to estimate the volume of text for translation. For example, bilingual documents such as contracts, technical instructions or price lists may contain both text information and many numbers. In order to accurately calculate the cost and time of order fulfillment, it is necessary to isolate the text part from the non-text part.
Data Analysis
Sometimes you need to analyze data that contains several languages. Removing Cyrillic can help you focus exclusively on Latin characters, which is important in the context of information processing, for example, for statistical or financial reports.
Data Cleaning
When working with documents, it is often necessary to clean data from unnecessary languages to make the data more homogeneous for further processing and analysis. This can be especially relevant for glossaries, where terminology analysis plays a large role.
Formatting and Standardization
When preparing texts for publication, you may need to remove certain characters and letters. When these are one or two characters, they can be removed by autoreplacement, but when there is a whole array of characters, you have to work with regular expressions.
There are various tools and methods for removing Cyrillic. Our website has a special module that allows you to quickly and efficiently remove Russian and English letters, leaving only numbers and other characters. This is achieved using regular expressions and software algorithms that automate the process.
Considering the variety of document types and the need for an accurate assessment of their volume and cost of translation, the developed modules help to simplify the work and significantly improve the quality and speed of providing translation and editing services.
