[ABBYY Aligner Portable Serial Key Keygen
Jamar Lizarraga
The application aligns texts in 10 popular European languages (English, German, French, Italian, Polish, Portuguese, Russian, Spanish, Turkish, and Ukrainian) with support for 90 translation directions. The resulting texts can be saved either in RTF or TMX format which are international standards supported by virtually any CAT tools. ABBYY Aligner opens files in TXT, RTF, PDF, HTML and documents created in popular Microsoft Office applications (DOC, DOCX, PPT, PPTX, PPS, PPSX, XLS and XLSX). It also supports pasting text from the Clipboard.
ABBYY Aligner is available at via flexible licensing options. A free, fifteen-day trial version which allows exporting up to 1000 rows (two matched segments per row) of aligned text into RTF and TMX formats is also available for download. For more information about the product and licensing, please visit www.abbyy.com/aligner.
Along with the desktop application, ABBYY has launched ABBYY Aligner Online, a special Web service for alignment of small parallel texts. It is designed for obtaining quick results when error checking and editing are not required. This service allows online export of up to 50 rows of the aligned text into RTF or Translation Memory (TM) databases free of charges. ABBYY Aligner Online finds matching segments in the source and translated texts in 10 European languages (English, German, French, Italian, Polish, Portuguese, Russian, Spanish, Turkish, and Ukrainian).
I am wondering wether or not to take the leap and buy Trados Studio and I'm hoping you can help me make the decision. I've been using an extended trial license for a few weeks and exploring the features, but I am still unsure if it's the right fit for the kind of work I do.
I've been translating contemporary romance from English into French for four years now and currently have over 80 books (from anywhere between 40,000 and 80,000 words each) under my belt. Contemporary romance is very much a defined genre, so the books are similar and can be repetitive even between authors. I was hoping to streamline my process by incorporating this growing corpus into Trados.
I've tried creating a TM, aligning a few books and importing them into the TM. I would do a cursory reading before Confirming All -- the alignment is mostly good, but there are mistakes. However it seems like aligning every segment manually would take me hours and hours per book (I tried!), and I don't see that being a viable option.
I'de like to be able to recycle segments and generate fuzzies when I pre-translate with Batch Task. Is that doable? And if so, should I set a specific alignment value when Advance Importing the alignment into the TM?
I tried pre-translating a chapter using my TM of about 10 books, and the results are quite absurd. Very few translations are generated (which is not that surprising considering my small TM), but single-word source segments (e.g. "Yes.") sometimes turn into full sentences from other books. So maybe a TM is not the way to go?
In addition to the usefulness of a TM, literary translators can benefit from other Trados Studio features, such as AutoSuggest Dictionaries (generated from TMs), termbases and AutoText. All of these are AutoSuggest providers and can both help save time and maintain consistency.
To answer your question about recycling segments and generating fuzzy matches (look into fragment matches as well): yes, that's exactly what you can get from a good TM. If your alignment efforts are not paying off so far, or you don't want to invest the time needed to clean up the alignments, you can always try manually translating one of your novels to feed your TM, and then use the TM for future jobs. As the TM grows, it will become more and more useful.
Absolutely. A CAT tool, and SDL Trados Studio for that matter, is the best friend and assistant for a literary translator. And no, "it does not limit the creativity" of the literary translator in any way, shape, or form. That reminds me of some writers who refused to use a "word processor" (that's how the software and the system were called back in the day) because of... (many whimsical reasons, I would guess). Herman Hesse and Thomas Mann wrote their monumental literary works using a typewriter, but that was many decades before the birth of the modern PC. Garca Mrquez, at some point, started using a Mac computer to write his novels... But I'm digressing.
Just a reminder, a translation memory (TM) does not translate for you, it just suggests for you and above all, it helps you remember how you translated a particular sentence, idiom, or whatever quirkiness of the source language. Just try to reuse your translations by aligning SL and TL texts. Best of all, take advantage of SDL MultiTerm to manage terminology. SDL MultiTerm is the best terminology management system of all CAT tools in the market, in my view.
SDL's alignment tool is only one option, and definitely not the best one. Other aligners you could try include ABBYY Align, LF Aligner (sourceforge), TM-TOWN aligner, AlignFactory Light, HunAlign (github), and Stingray Document Aligner. Also, other CAT tools have their own aligners that might work better for you.
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Text alignment of multilingual documents is one of the most widely used procedures in our industry. Alignment is a process that allows creating translation memories from already translated documents. This can be very useful to leverage previous work and improve consistency and productivity. However, as we will see in this article, alignment has other uses.
This procedure is usually a double-edged sword: while it helps us to recover old translations that have not gone through a CAT tool and thus reuse the content, doing it incorrectly can result in spending too much time on the process to obtain quality and reusable alignments and therefore be a completely counterproductive tool.
- The two documents must be in the same format. This is explained by understanding how the process works. What would happen if we try to align an original document in PDF with a translated document in DOCX? The aligner would try to understand the structure of the text, segment it according to some segmentation and format rules and use patterns to make that text match in both languages. The segmentation and format can be very compromised when creating those patterns if the file formats are different from each other and the result would be something unusable or with a huge editing requirement before being ready for production.
- The segmentation rules have to be as standard as possible for both languages. By this I mean that if in language A we segment after colons (:), we cannot avoid the segmentation of the colons in language B, we would create inconsistent translation units and it would be more difficult to find the alignment pattern.
- Similarly, although I am a big fan of comma segmentation for my translation fields, comma alignment is usually quite a disaster because it does not usually match between languages. Also, paragraph segmentation would be unproductive if we then are not going to translate text segmented by paragraph. The ideal is to segment by sentence.
- If we want to make the most of our alignments in our projects, it makes no sense to align text without tags or with different tag handling if later our text to translate will have them or in a different way. Therefore, tag handling is very important because it will require less editing when we use the alignment.
1. The first thing is to get the documents in the same format and, in addition, in a format that is CAT tool friendly. If we have PDF we will use optical character recognition (OCR), if we have CSV, we will convert it to XLSX, and so on with all file formats.
2. Next, we must format the documents so that they are as similar as possible. This means that, if we use OCR to convert two documents to DOCX, we have to edit and format both texts in Word so that those texts have exactly the same appearance.
3. The next step is optional, but I highly recommend it because we will make sure to have full control of the segmentation and tag handling. Use your CAT tool to create two projects, one for Text A and another for Text B. From those projects we obtain the corresponding XLIFF files, thanks to this step, we can detect any discrepancy in the segmentation and we can mimic our CAT tool tag handling.
And when you click on OK, the Autoaligner runs, there you have several options that you can modify until you get a more than decent automated result. It is important to keep in mind that, since our XLIFF files were already segmented previously, so that OmegaT does not resegment those files, we uncheck that option and thus maintain the original segmentation of the XLIFF files.
It is very important to point out that the alignment may still have some errors and it is very convenient to review the TMX in a translation memory editor such as Heartsome TMX Editor or to apply some penalty to the translation memory at the time of use to avoid autopopulation of erroneous translation units.
Bitext2tmx is a program written in Java (and therefore cross-platform) that allows to segment and align corresponding translated sentences from plain text files and generate a TMX translation memory for use in computer-assisted translation applications.
The program is quite straightforward: once you have two TXT files (the source document and the corresponding translation) open Bitext2tmx, then choose File > Open, choose the source and target TXT files and set the relevant languages and encodings (UTF-8 is supported).
The text files are opened in the program window, where you can fine-tune the alignment by joining, splitting or deleting rows. There is also a command for deleting empty rows.When the text looks properly aligned, choose File > Save as to save the aligned texts as a TMX (v 1.1) memory file that you can then import into the translation environment of your choice.
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