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Showing posts with label translation. Show all posts
Showing posts with label translation. Show all posts

qLabel: Multilingual content without translation

Tuesday, April 1, 2014

Today we are happy to release qLabel, an open source JavaScript library that looks up and displays the labels of entities marked-up in a Web site in the language of the user. You can use qLabel in any Web document - below are some examples of where it might come in handy.

Some web sites provide content in a very structured form - think of restaurant menus, schedules, images with textual annotations, catalogs, etc. For example, this is a map of the inhabited continents:
Providing this content in different languages is as easy as looking up how all the mentioned entities in the SVG map are named in the other language. If we want to display the content in German, we need to know that South America is Südamerika in German and replace it.
The same works for Chinese:

Or, to take a language that Google Translate does not support yet, such as Uzbek:

The labels that we have used so far are from Wikidata, a sister project of Wikipedia launched in 2012. Wikidata supports more than 300 languages, but there aren't labels for all entities in all languages yet. Let’s take a look at Hindi:
We see that the Hindi name for Australia is still missing. But adding that is as easy as going to the Hindi view of Wikidata for Australia and add the label, and likely by now someone has already fixed it (and that would be visible here if those images above would indeed be embedded SVGs instead of PNG files - see the live map demo). You can improve the content in Wikidata and make more knowledge accessible to everyone.

In these cases, there is no need for intelligent translation algorithms in order to translate the Website: it is enough to look up the label for the mentioned entities in the language of the reader and display them in place. qLabel does exactly that.

The Website author annotates the entities mentioned in the page with unique identifiers, and qLabel looks up the name for these entities in the language requested by the user and displays them. No need to wait until your translation service of choice supports your language, it only depends on the underlying lexicon of entities and the languages they support.

Every entity is marked up with a URI, which is then used to look up the labels in the requested language. Take a look at the examples: the above map, a tournament schedule, a food menu, and tour dates. You can use any URI that supports look-up using Linked Data standards, in particular Google’s Freebase and Wikidata, but you can also publish your own set of entities and labels as RDF or JSON-LD and use them — and at the same time releasing them to the Semantic Web!

Read more about qLabel and how you can use it. Contributions to the code base are more than welcome, the source code is on Github.  Let us know about how you use qLabel!

Thanks and kudos to rdfquery, Wikidata, any23, Freebase, Universal Language Selector, the Wiki Atlas, and the Wikidata Multilingual Picture Dictionary.

By Denny Vrandečić, Ontologist, Google Knowledge Graph 

Localize your apps and content more easily -- new formats in Translator Toolkit

Friday, March 30, 2012


At Google, we put a lot of energy into helping localize the world’s information to make it more useful to more people. It’s not just about localizing our own products -- we want to provide tools that make it easy for translators and developers around the world to localize their own apps and content. Google Translator Toolkit is our online translation tool for amateur and professional translators -- it’s built on Google Translate and supports more than 100,000 language pairs.

This week, the Translator Toolkit team has launched support for four new translation-related file formats:
Android Resource (.xml)
Application Resource Bundle (.arb)
Chrome Extension (.json)
GNU gettext-based (.po)

With these new file formats, you can use Translator Toolkit to localize your apps and other products and content much more quickly and easily.

For example, to translate your Android application, go into the res/values directory and upload strings.xml into Translator Toolkit -- Translator Toolkit will now automatically translate it. You can then share your translations with amateur or professional translators, who can localize the text using Translator Toolkit’s WYSIWYG online editor.


When you’re finished, you can export your translated application and store it in a locale-specific directory in Android. Voilà -- easy localization! 翻译起来太方便了!

In addition, we’ve made the Translator Toolkit interface more intuitive for these new file formats so users can translate faster and more accurately. For example, you can turn on ‘Customized colors’ so translators can annotate the edited segments, ‘Number of characters in the segment’ to make sure the text doesn’t run too long (very important for mobile devices), and ‘Synchronized scrolling’ so you can scroll the original and translated text at the same time, which makes navigation much easier.



With these new file formats and UI features, along with the file formats we already support (.aea, .srt, .html), we hope Translator Toolkit can help you reach more users around the world.

When you’re ready, give Google Translator Toolkit a try and suggest any improvements you’d like to see so we can work on making it even better.

Posted by Chris Yang, Product Manager and Haidong Shao, Software Engineer, Translator Toolkit

The Apertium Project's First Google Summer of Code

Friday, November 27, 2009

The Apertium Project works on open-source machine translation and language technology. We try to focus our efforts on lesser-resourced and marginalized languages, but also work with larger languages. To date, we have released translators for 21 language pairs, covering languages spoken by 1.1 billion people, ranging from English (est. 500m speakers) to Aranese (est. 4,000 speakers). A similar number of additional language pairs are in development. The Apertium software is licensed under the GPL, but in addition (a rarer situation in the machine translation field) so is the data for all these language pairs. This means that the data can be re-used by other language projects (e.g. in developing spelling or grammar checkers, thesauri, etc).

This was our first year in Google Summer of Code and we were very fortunate to receive nine student slots. We filled them with some great students and are pleased to report that out of the nine projects, eight were successful.

The completed project were:

A translator for Norwegian Bokmål (nb) and Norwegian Nynorsk (nn)

This project was accepted as part of our "adopt a language pair" idea from our ideas page. Some work had already been done on the translator but it was a long way from finished. Kevin Unhammer from the University of Bergen was mentored by Trond Trosterud from the University of Tromsø. The final result, after an epic effort, is a working translator (and the first free software translator for nb-nn) that makes a mistake in only 11 words out of every 100 translated, making using the system for post-edition feasible.

One of the key aspects of Kevin's work was the re-use and adaptation of existing open source resources. Much of the bilingual dictionary was statistically inferred from the existing translations in KDE, using ReTraTos and GIZA++ (created by Franz Och). In addition to this, Kevin used the Oslo-Bergen Constraint Grammer, contributing fixes not only to that, but to the VISL CG3 software itself. After the GSoC deadline, Kevin has continued his work, including incorporating some changes from feedback from the Nynorsk Wikipedia.

A translator for Swedish (sv) to Danish (da)

Another language pair adoption, Michael Kristensen, who had previously done some work on this translator, was mentored by Jacob Nordfalk, the author of our English to Esperanto translator. As there are very few free linguistic resources for Swedish and Danish the work was pretty much started from scratch, although we took great advantage of the Swedish Wiktionary. The translator is only unidirectional, from Swedish to Danish, and it has an error rate of around 20%.

The completion of this translator is something of a triumph for Apertium. Begun back in 2005, the project had been neglected for many years. This was the first translator for the Apertium platform that focused on non-Romance languages.

Multi-engine machine translation (MEMT)

Gabriel Synnaeve was mentored by Francis Tyers to work on a module to improve the quality of machine translation by taking translations from different systems and merging their strengths and discarding their weaknesses. The two systems focused on in the initial prototype are Apertium (rule-based MT) and Moses (statistical MT) but it can easily be extended to more. The idea behind the system is that for some languages there is often not one MT system which is better than all others, but some are better at some phrases and some are better at others. Thus, if we can combine the output of two or more systems with different strengths/weaknesses, we can make better translations.

Perhaps the most exciting aspect of the MEMT project is its potential for use as a research platform for future work on hybrid machine translation, by allowing the researcher to focus only on the algorithms they wish to implement. During the project, Gabriel was joined by Francis in person for a 'mini-hackathon', which, despite something of a farcical start involving requests made on IRC for phone calls across Europe on behalf of two people who were in the same city, lead to a greater degree of functionality and modularization in the code.

Highly scalable web service architecture for Apertium

Víctor Manuel Sánchez Cartagena
worked with mentor Juan Antonio Perez-Ortiz on a highly-scalable web service architecture, or, Apertium for Cloud computing. Initially targeting Amazon's EC2, as well as standalone servers, the scalable web service allows the use of multiple translation services on multiple physical or virtual servers, scaling to meet the translation demands of users, from a single user-facing service, which implements the Google Language API.

The core of the system is the translation router, which controls the flow between user and translation server, based on a variety of factors, including the availability of the language pair, the current load on the server, as well as providing a framework to allow these factors to have different priorities on a per-user basis. It also takes into account the cost of each translation request. The project is a complete package; as well as the router, it includes a translation daemon, and convenience scripts to ease the rollout of server instances.

In addition to his work on his project, Víctor is also serving as an organiser for the FreeRBMT workshop.

Conversion of Anubadok


Abu Zaher was mentored by Kevin Donnelly and Francis Tyers to convert Anubadok, an open-source MT system for English to Bengali to work with the Apertium engine. This was an ambitious project and not all of the goals were realised, but we were able to make the first wide-coverage morphological analyser / generator for Bengali and a substantial amount of lexical transfer, so the project was a great success.

Zaher is also looking at improving the Ankur spell checker with information from his analyser / generator, so the work done is already being reused; there is also interest in using the data to create a Bengali stemmer, for more efficient searching/indexing of Bengali texts, and a number of tools which were created to model the various aspects of Bengali inflection will certainly prove useful in other areas of NLP for Bengali.

Apertium going SOA

Pasquale Minervini's work was motivated by the needs of Informatici senza Frontiere to have a translation engine that would fit into a Service-Oriented architecture. To this end, Pasquale, mentored by Jimmy O'Regan, designed an XML-RPC-based server that efficiently contains the Apertium pipeline, and layered it with JSON (still under development), SOAP, and CORBA services, which, as well as making Apertium more buzzword compliant, gives a greater range of options to programmers wishing to integrate Apertiums translation services into a wider range of architectures. This is undoubtedly a popular project idea: Alexa's keywords for Apertium show 'apertium going soa' and 'deadbeef apertium' (deadbeef is Pasquale's IRC nick) in 2nd and 4th place for search keywords leading to Apertium.

Because of the potential overlap between their projects, in the first weeks of their GSoC work, Pasquale and Víctor agreed on the Google Language API as a standard for their projects to communicate; Pasquale took this agreement one step further by implementing the 'language detection' feature of the API - something previously unavailable in Apertium. In addition to that, Pasquale also contributed memory leak checks against the Apertium platform, as well as other fixes, and has helped another (non-GSoC) student in the goal of porting Apertium to Windows.

Trigram part-of-speech tagging

Zaid Md. Abdul Wahab Sheikh
was mentored by Felipe Sánchez Martínez to improve our part-of-speech tagging module to use trigrams instead of bigrams, as well as implementing changes to the training tools to create data for it.

Apertium was originally designed for closely related languages, but is growing to meet the challenges of translating between more distant languages. One of the unique aspects of Dr. Sanchez's work on Part-of-Speech tagging is the use of target language information which allows an accurate tagger to be trained using much less data than usual. Zaid's work builds on Dr. Sanchez's work with first-order Hidden Markov Models, extending it to second-order HMMs, similarly to TnT. This enables more accurate translation between more distant languages, using the same methods, so that the rest of the Apertium system can continue to grow.

Java port of lttoolbox

Raphaël Laurent worked with Sergio Ortiz Rojas to port lttoolbox to Java. lttoolbox is the core component of the Apertium system; as well as providing morphological analysis and generation, it also provides pattern matching and dictionary lookup to the rest of Apertium, so a Java port is the first step towards a version of Apertium for Java-based devices. Raphaël finished an earlier line-for-line port contributed by Nic Cotrell, first making it work; then making it binary compatible.


As it stands currently, lttoolbox-java can be integrated into other Java-based tools, facilitating the re-use of our software and our extensive repository of morphological analysers. Tools such as LanguageTool, the open source proofreading tool, also make extensive use of morphological analysis, but OmegaT, the open source CAT tool, could use it for dictionary look-up of inflected words; it could even be used with our own apertium-morph tool: a plugin for Lucene that allows linguistically-rich document indexing.

FreeRBMT

On the 2nd and 3rd of November, we held the first FreeRBMT workshop, which was heavily inspired by the Google Summer of Code program, both as a way for students and mentors to meet in person, and to provide the students with an opportunity to present peer-reviewed papers about the work they completed during the program. The entire proceedings are available from the University of Alicante; in particular, we would like to highlight the papers which were successfully presented by the students who took part in GSoC:

Apertium goes SOA: an efficient and scalable service based on the Apertium rule-based machine translation platform; Minervini, Pasquale

Development of a morphological analyser for Bengali; Faridee, Abu Zaher Md.; Tyers, Francis M.

An open-source highly scalable web service architecture for the Apertium machine translation engine
; Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio

Reuse of free resources in machine translation between Nynorsk and Bokmål; Unhammer, Kevin; Trosterud, Trond

A trigram part-of-speech tagger for the Apertium free/open-source machine translation platform
; Sheikh, Zaid Md Abdul Wahab; Sánchez-Martínez, Felipe

In addition, the following paper was presented by the mentors of a successful project (Michael, the student, was unfortunately too busy to participate in its writing):

Shallow-transfer rule-based machine translation for Swedish to Danish; Tyers, Francis M.; Nordfalk, Jacob



We would like to thank Google for providing us with the opportunity to participate in the Summer of Code program; in particular, Leslie, Cat, and Ellen, for making it run so smoothly. We would also like to make special mention of two students: Ankitha Rao and Daniel Beck, who, despite being unsuccessful in their applications, continued to work on their proposed projects (an English to Hindi translator, and a module for multi-word units, respectively). Finally, we would like to thank all of the students, mentors, and administrators who contributed their time and skill to Apertium.


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