About Machine Translation
Machine Translation: An Introductory Guide. By Doug Arnold, Lorna Balkan, Siety Meijer, R.Lee Humphreys and Louisa Sadler (1994). "The topic of the book is the art or science of Automatic Translation, or Machine Translation (MT) as it is generally known --- the attempt to automate all, or part of the process of translating from one human language to another. The aim of the book is to introduce this topic to the general reader --- anyone interested in human language, translation, or computers."
Scaling the Language Barrier. By Sebastian Rupley. PC Magazine (July 13, 2004). "In the annals of computer comedy, one of the most famous anecdotes is about asking a speech recognition engine, 'Recognize speech?' The translation comes back: 'Wreck a nice beach.' Getting machines to understand both spoken and written language has been an elusive goal for the tech industry for many years. Now, thanks to a wave of government funding and technical breakthroughs, machine translation (and understanding) of written language is getting unfunnier by the minute. ... The one clue Meaningful Machines has given about its software is that it will use new methods of statistically ranking the likelihood of what entire phrases mean, rather than just translating one word at a time. That allows it to discern whether the word baseball in a given phrase refers to a ball or a game. ... Carnegie Mellon University, the University of Southern California, and Microsoft Research operate some of the largest programs for developing machine translation software. Microsoft is primarily focused on extracting meaning from documents in English."
E-translators - the more you say, the better, By Gregory M. Lamb. The Christian Science Monitor (April 22, 2004). "Universal translation is one of 10 emerging technologies that will affect our lives and work 'in revolutionary ways' within a decade, Technology Review says."
Computer aid ensures speedy, high-quality translations. IST Results (January 12, 2005). "Increasing translators? productivity is the goal of TransType2, an innovative computer-aided system that allows rapid and efficient high quality translations. Due to end in February, the 36-month IST programme project has drawn on two of the most commonly used translation technologies developed to date: Computer-Assisted Translation (CAT), in which human translators work in unison with a computer; and Machine Translation (MT), in which the computer handles the entire process. While both techniques have advantages and drawbacks, TransType2 has 'used the best of both worlds' says project manager José …steban at Atos Origin in Spain."
Software learns to translate by reading up. By Will Knight. NewScientist.com news service (February 22, 2005). "Translation software that develops an understanding of languages by scanning through thousands of previously translated documents has been released by US researchers. Most existing translation software uses hand-coded rules for transposing words and phrases. But the new software, developed by Kevin Knight and Daniel Marcu at the Information Sciences Institute, part of the University of Southern California, US, takes a statistical approach, building probabilistic rules about words, phrases and syntactic structures. The pair founded a company called Language Weaver in Los Angeles, US, to sell the software as an automated translation tool."
The Translation Challenge. By Chip Walter. Technology Review (June 2003). "Researchers are making progress today using three basic approaches drawn from natural-language processing. Knowledge-based machine translation, for example, relies on human programmers to write lists of rules that describe all possible relationships between verbs, nouns, prepositions, and so on for each language. ... A second approach, example-based systems, relies chiefly on raw computing power. ... Statistical techniques also depend on computing power to compare reams of previously translated text. However, this strategy selects the most likely translation using sophisticated mathematical models that the software continually upgrades based on how often its interpretations prove accurate."
Scaling the Language Barrier. By Sebastian Rupley. PC Magazine (July 13, 2004). "In the annals of computer comedy, one of the most famous anecdotes is about asking a speech recognition engine, 'Recognize speech?' The translation comes back: 'Wreck a nice beach.' Getting machines to understand both spoken and written language has been an elusive goal for the tech industry for many years. Now, thanks to a wave of government funding and technical breakthroughs, machine translation (and understanding) of written language is getting unfunnier by the minute. ... The one clue Meaningful Machines has given about its software is that it will use new methods of statistically ranking the likelihood of what entire phrases mean, rather than just translating one word at a time. That allows it to discern whether the word baseball in a given phrase refers to a ball or a game. ... Carnegie Mellon University, the University of Southern California, and Microsoft Research operate some of the largest programs for developing machine translation software. Microsoft is primarily focused on extracting meaning from documents in English."
E-translators - the more you say, the better, By Gregory M. Lamb. The Christian Science Monitor (April 22, 2004). "Universal translation is one of 10 emerging technologies that will affect our lives and work 'in revolutionary ways' within a decade, Technology Review says."
Computer aid ensures speedy, high-quality translations. IST Results (January 12, 2005). "Increasing translators? productivity is the goal of TransType2, an innovative computer-aided system that allows rapid and efficient high quality translations. Due to end in February, the 36-month IST programme project has drawn on two of the most commonly used translation technologies developed to date: Computer-Assisted Translation (CAT), in which human translators work in unison with a computer; and Machine Translation (MT), in which the computer handles the entire process. While both techniques have advantages and drawbacks, TransType2 has 'used the best of both worlds' says project manager José …steban at Atos Origin in Spain."
Software learns to translate by reading up. By Will Knight. NewScientist.com news service (February 22, 2005). "Translation software that develops an understanding of languages by scanning through thousands of previously translated documents has been released by US researchers. Most existing translation software uses hand-coded rules for transposing words and phrases. But the new software, developed by Kevin Knight and Daniel Marcu at the Information Sciences Institute, part of the University of Southern California, US, takes a statistical approach, building probabilistic rules about words, phrases and syntactic structures. The pair founded a company called Language Weaver in Los Angeles, US, to sell the software as an automated translation tool."
The Translation Challenge. By Chip Walter. Technology Review (June 2003). "Researchers are making progress today using three basic approaches drawn from natural-language processing. Knowledge-based machine translation, for example, relies on human programmers to write lists of rules that describe all possible relationships between verbs, nouns, prepositions, and so on for each language. ... A second approach, example-based systems, relies chiefly on raw computing power. ... Statistical techniques also depend on computing power to compare reams of previously translated text. However, this strategy selects the most likely translation using sophisticated mathematical models that the software continually upgrades based on how often its interpretations prove accurate."
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