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When the Soviets successfully placed
"Sputnik," the first satellite, into earth orbit in 1957, it took America by surprise. Behind the scenes, the news was more distressing because technical details of the satellite had actually appeared months before its launch in a Soviet hobby magazine. However, it had gone unnoticed because American intelligence did not have the means to quickly translate Russian to English.
While not nearly as high profile or
sexy as the race to the moon in the 60s, the government also set out to achieve automatic translation of Russian into English, dumping millions into academic and industrial MT research. Agencies, such as the CIA, relished the thought of having immediate access to thousands of Soviet papers and publications, with an eye on the huge advantage it would give them in counter-intelligence.
Unfortunately, almost a decade and
20 million dollars later, results were not meeting these overly optimistic expectations. In 1966, the Automated Language Processing Advisory Committee (ALPAC) issued a highly critical report, citing the lack of significant progress, which effectively halted government spending on MT.

Star Trek - Universal Translator

In part, one can attribute the
apparent failure of MT research to the unrealistic expectations set in this field's early days. The public's first general introduction to the concept of MT came from the classic 1960s TV series Star Trek, where the crew of the starship Enterprise used a device called the "Universal Translator" to communicate with alien races across the galaxy.
With little more than a few snippets
of dialogue from a newly encountered race of sentient beings, the Universal Translator deduced the meaning of their languages entire lexicon and flawlessly, in near real time, translated speech. In retrospect, not only was this unrealistic for the times, but a downright impossible goal.
Fully automatic, high quality
text-to-text Machine Translation across vastly different knowledge domains is challenging. However, throw in a scarcity of training data and speech-enabled front and back ends, and the ideal symbolized by the Universal Translator becomes unachievable even with today's best technology. Due to overly optimistic expectations and a subsequent collapse of government funding, research into MT survived in only a few institutions that could afford going it alone, such as IBM and strangely enough -- the Mormon Church.

The Mormon Connection

In the late 1970s, the Church of
Latter Day Saints undertook a massive MT project in hopes of making it relatively
easy to translate their religious literature into different languages. A key figure in that effort was Steve Richardson, first an undergraduate and then graduate student at Brigham Young University in Provo, Utah, who used his computer science and linguistic education to further the Mormon MT effort.
Upon completion of his bachelor's degree in 1977,
Richardson worked full-time for the Mormon MT project until he completed his master's degree in 1980. At that point, after five years, they canceled the undertaking. Although not successful at producing cost-effective MT because of the high cost of computing power on the IBM mainframes, the project inspired a number of MT start-ups in the Utah area, the descendents of which continue in operation today. With a growing family to support, Richardson took a job as an associate programmer with an IBM product group in Endicott, New York.

The IBM Connection
In 1983, Richardson contacted a group at IBM's famous
T. J. Watson Research Center, dedicated to pushing the limits of natural language processing. Richardson met George Heidorn and Karen Jensen on an incredibly snowy day in mid-February. "I remember my first meeting with Karen and George clearly, on February 11, 1983, because it was snowing so hard that the Watson Research Center had to close," says Richardson.
Heidorn was the manager of the Natural Language
Processing group at IBM Watson and Jensen, a leading authority in English grammar, his close colleague. Heidorn, Jensen, and Richardson formed a powerful trio of talent that weathered many technical and corporate storms to eventually build their shared dream - one of the largest and most successful Natural Language Processing (NLP) Projects in the world.
In the 1980s, government and industry funding was
again flowing for MT research and development. The launch of the Japanese Fifth Generation Project, aimed at building an intelligent computer within 10 years, was the equivalent of another "Sputnik-scare,"spurring the U.S. government to again open its purse strings for MT research. This funding launched large-scale efforts, such as CYC (short for encyclopedia), to create software capable of understanding natural language via common sense reasoning.
Realizing the need to demonstrate the practical
application of their NLP Project, the IBM trio transferred to Big Blue's development side, with hopes of including a grammar checker in a software suite tentatively dubbed "OfficeVision," intended to compete directly with Microsoft's highly successful Office.

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