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
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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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