GIGO (Garbage In, Garbage Out) As with software, if the data fed into the computer program (read source text) is bad, the program's results (read translation) will also be bad.
I thought of this when reading ultan's recent post "Information Quality, MT and UX" on Multilingual Computing's Blogos blog. ultan notes that quality information not only makes machine translation easier, but simply is better information that is more easily understood by both humans and machines. So what is quality information? I think quality information consistent and concise, but well-written text with an audience-appropriate level of technical terminology. In this context, well-written refers to grammatically correct, clear structures free of spelling and punctuation errors.
Clearly the amount and complexity of subject-specific terminology used depends on the text's end users. However, such poorly written source text not only hampers the flow of reading, it often also adds ambiguity to the text. The Coming Disintermediation and Disruption in the Translation Industry. I spent a few days in a very hot and dry Las Vegas last week at the IMTT Vendor Management Seminar, which I would wholeheartedly recommend to anybody who wants to understand how to better manage the relationship with translators to mutual benefit and also get a sense for changing production models in the industry.
What is Holding the Wider Adoption of Machine Translation (MT) back? I have been seriously distracted the last few weeks by the World Cup which is really the only sporting event I really ever connect to anymore.
This year I watched more games (in HDTV too) than I have since my childhood and I am glad that the clearly better team won the final. My opinion on the real winners: Germany, Uruguay, Spain and Ghana, the biggest and possibly worst loser in World Cup history: The Netherlands. Anyway, there is an interesting discussion in the LinkedIn MT forum started by Lori Thicke that I thought was worth summarizing and highlighting.
Facebook: From 1 to 100 languages in two years. Social Translation : Using the WWL API To Build Multilingual Sit. Language is one of the few remaining barriers on the Internet. The web has rendered time and distance largely irrelevant, but much of it remains fragmented by language. The Worldwide Lexicon , an open source project I have worked on for some time, aims to lower those barriers by combining people and computers to participate in translating and curating web content. We're releasing a new web services API, hosted on Google's cloud computing platform, that makes it easy to embed social translation features in virtually any website or web app. This tutorial explains how to build a variety of translation tools using straightforward web services development techniques.
If you're interested in a review of Google's App Engine platform, see my companion post, Why I Started Coding Again (Thanks Guido!) Wait till I come! » Blog Archive » Translating or localising doc. Friday, December 19th, 2008 at 6:02 pm We just had an interesting meeting here discussing plans of how to provide translations of our documentations in different languages.
I am a big fan of documentation and have given several presentations talking about the why and how of good docs. NLA Machine translation (MT) Urdu software. NLA Machine translation (MT) Urdu software NLA launches Urdu software to break language barriers Islamabad, July 19: English is no more a barrier in learning computer and internet technology as National Language Authority (NLA) on Saturday released and Urdu software carrying computing and processing systems, developed by its Centre of Excellence for Urdu Informatics.
Machine translation (MT) software is a big step and now Urdu Data House is ready to replace other National languages on cyber space, NLA Chairman Iftikhar Arif announced in a ceremony. "Microsoft applications like Windows, Office are now converted into Urdu operating systems. MT on the Slope of Enlightenment? Evaluating Machine Translation:The Present and Future of Multili. A recent study conducted by researchers at The University of Granada’s School of Translation and Interpretation attempts to analyze and evaluate the results of machine translations done with popular online tools such as Google Translator, Promt, and WorldLingo.
The study was published in this month’s issue of Translation Journal, and it raised interesting questions for me about the possible uses for online machine translation. Looking at the findings, it should come as no surprise that all of the machine translation tools produced poor results in terms of the number of errors, or that after the translations passed through a round of human editing, the number of errors were drastically reduced. What is interesting, though, is that certain online tools performed better than others, and specific language combinations produced varying results. The graph below shows results from German into Spanish (the researchers used EvalTrans Software). An open-source shallow-transfer machine translation engine and t.
Untitled. Do You Speak International? - Gill Corkindale - Harvard Business. By Gill Corkindale | 3:58 PM June 28, 2007 I may be in the minority here, but has anyone else noticed the strange things that have been happening to English lately?
I don’t mean business speak or management and technical jargon, but the way we are all starting to speak “international.” The lingua franca of the business world has gone global. More people are speaking English today — but are we all speaking the same language? I ask this question because recently I have found myself struggling to follow some conversations between executives from different countries. Can you translate 34,501 words in 10 hours? An SDL advertisement in 2009 claimed that one person translated over 34,000 words in a 10 hour period using the new SDL Trados product release.
The logic in the ad: buying a Trados license is a no-brainer and the expense can be recouped quickly. Many people, however, were upset by that ad and called it false advertising. You can read the discussion here. Close to 100 comments were written until the discussion was closed for further comments. Welcome back, Yeeyan. If I had to pick a project that most excited me in 2009, it would be Yeeyan, a distributed translation project focused on making influential English-language media accessible to a Chinese-speaking audience.
Yeeyan’s founders built a community that included thousands of translators and struck partnerships with content providers like The Guardian, giving them permission to publish translated content. I was particularly struck by the talk Yeeyan cofounder Zhang Lei gave at the 2009 China Internet Research Conference at UPenn Annenberg – he made it clear that the motivation behind Yeeyan was a desire to use translation as a bridge between cultures, letting Chinese and English-speakers see the world from each other’s perspective.
I was singing the project’s praises to a journalist last week when he pointed out that Yeeyan’s website was down. Danwei’s article on Yeeyan’s closure gives a sense for how abrupt the move was. What every mass marketer needs to learn from Grouch. Perhaps the most plaintive complaint I hear from organizations goes something like this, "We worked really hard to get very good at xyz.
We're well regarded, we're talented and now, all the market cares about is price. How can we get large groups of people to value our craft and buy from us again? " Apparently, the bulk of your market no longer wants to buy your top of the line furniture, lawn care services, accounting services, tailoring services, consulting... all they want is the cheapest. The middlemen: how translators are boosting India's writers - Th. "Good enough" machine translation - Windows Live. At Localization World 2008 in Madison I heard many remarks on how machine translation cannot compete with human translation, MT with human post-editing is not increasing productivity and how in general raw MT is only appropriate for "not so important" content like support articles. Many good points, but I couldn’t shake the feeling that it could not be that bad. Returning from Madison I ate Chinese food at the Detroit airport and my chopsticks came in this wrapper: I had a good laugh.
Videos uploaded by asiaonline. Untitled. Ideas. Better Translating Service the problem of making an intelligible automated translation -- much more one that's actually reasonable-sounding -- is not easy, and it's not exactly solved anywhere. the proposal is to make translations more direct and decipherable by not "sugar-coating" them trying to put them into regular English (or any other recipient language obviously) grammar. For example, Mandarin grammar is *completely* different from English grammar. When translating from Mandarin, notation (brackets, etc.) could be used instead of normal English grammatical structures to relay the grammatical structure of the Mandarin phrase. Most people aren't too stupid to get the hang of such a system after a couple of translations; the bigger problem is simply not knowing the words of another language. Tolingo secures Series A funding for fast, cheap translation ser.
[Germany] Tolingo, the online translation platform, has secured a Series A round of investment. The investment comes from Neuhaus Partners in Hamburg which is using a local start-up fund run by a public programme in conjunction with the local KfW bank (hey, this is Europe remember). The investment will be used to expand further in Europe and internationally. The Italian Job. January 14th, 2010 by Tommaso De Benetti If you’ve ever holidayed in Italy, you might have noticed that many of the locals, even in popular tourist spots, struggle with English.
There are probably a number of causes for this phenomenon, such as a rusty education system and the all southern conviction that “you don’t really need English anyway”, but perhaps the major reason why the Italians and other Southern European countries struggle is the habit of dubbing popular TV shows and movies into their native tongue. Machine Translation – articles for reading « Communicate Digital. Casacuberta, F., Civera, J., Cubel, E., Lagarda, A., Lapalme, G., Macklovitch, E., et al. (2009). Untitled. Collaboration. Or... Unprofessional Translation. Swedish translation system gets EU funding. Published: 19 Jan 2010 17:19 GMT+01:00Updated: 19 Jan 2010 17:19 GMT+01:00 A research group led by the University of Gothenburg in the west of Sweden, has been granted 25 million kronor ($3.5 million) in EU funding to develop an online multilingual translation system covering most European languages. The system, which can translate a number of languages simultaneously, will be more accurate and reliable than existing programmes, says Aarne Ranta, professor of computer science and engineering at the University of Gothenburg.
Synaptic Web: Realtime is Just the Beginning. Guest Post by Chris Saad (@chrissaad | Blog)Vice President, Strategy, Echo. Crowdsourcing Tools. Untitled. Fanlation ~ English to French translations. January 20, 2010 Fanlation is a term that I've come across very recently, and I came across it again when I received Jost Zetzsche's Tool Kit newsletter: Welcome to UNTERM. Darpa Looks to Build Real-Life C3P0. Right now, troops trying to listen in on enemy chatter rely on a convoluted process.
They tune into insurgency radio frequencies, then hand the radio over to local interpreters, who translate the dialogues. Machine Translation Terminology - SDL Blog. A Translatours Catechisme (II): A New Drill : : Translation Guy. Translation As a Force of Change. Ushahidi & The Unprecedented Role of SMS in Disaster Response – Rule-based MT vs. Statistical MT: Does it Matter? Malaproprisms From The Bully Pulpit - 13 Translation. About MT & smartphones, speech recognition and hybrids « Pangean. Collaborative Translation by Monolinguals with Machine Translato. Chinese restaurant menu translation - oh oh.. Interview with Edith Grossman at The Boston Globe « By The Firel. Putting Google to the Test in Translation - Graphic - NYTimes.co. Google’s Translator Toolkit Is Helping The Machine Become A Bett.
Consider the Luddites. The Ongoing Quest for “Best” MT Translation Quality. Blog: Offering Your Content in 100 Languages. Machine Translation « Communication Desideratum. Some things are better lost in translation. The state of OmegaT. Launchpad Translations. Blogos. Machine and Human Translation 2: Recycling COMAL. When machine translation and volunteer translators collide: A Yo. Web Innovation Project » Is Machine Translation Coming of Age? About Us. Notes and reflections from the Open Trans. Global Voices Online » Global Voices Author Demographics 2010. The tradeoff between open and closed cdixon.org – chris dixon's. Falling Translation Prices and Implications for Translation Prof. Posts. The incredible shrinking delivery times. Freelance Translators Talk about Machine Translation « CETRAblog. Adobe launches translation crowdsourcing in China. No Monkeys! Lost in Translation.