|[November 28, 2012]
The International Computer Science Institute (ICSI) Leads Team Researching Ways to Build Speech Recognition Systems for New Languages Under Severe Data and Time Constraints
BERKELEY, Calif. --(Business Wire)--
The International Computer Science Institute (ICSI) is leading a
research team under the IARPA Babel Program that is focused on building
speech recognition solutions with self-imposed time and data limitations
for a variety of languages. The work aims to better understand
fundamental challenges and discover new methods for development of
speech models for languages that could emerge as important in the future.
"The goal of the Babel program is to rapidly build speech recognition
systems to support effective keyword search for new languages using
limited amounts of transcribed speech recorded in real-world
conditions," said Mary Harper, the IARPA Program Manager in charge of
the Babel program.
Using only a fraction of the training data usually required, the team
aims to build speech recognition systems for several languages in just
one week by the end of the program.
"ICSI excels at intellectual challenges and unique approaches to
research. This is an intriguing project that puts significant
constraints on our researchers as a means to discover better ways to
develop automatic speech recognition systems," said Roberto Pieraccini,
director and president of ICSI.
By working on a variety of languages with time and data restrictions,
the team will research basic principles of speech technology rather than
incremental improvements to existing technology. In addition, this
research will be useful in enabling keyword-search systems for those
languages that do not have large amounts of transcribed audio.
"The speech recognition systems we've built in the past have the curse
of being reasonably good, particularly for a few languages and speech
recorded in good acoustic conditions, which has often reduced the
impetus to significantly change the technology," saidProfessor Nelson
Morgan, deputy director and leader of the Speech Group at ICSI. "This
project strongly pushes us to solve fundamental problems in speech
recognition to address the Babel challenge."
In each of the four periods of the project, the team will be given a set
of languages and will be tasked with developing methods to quickly build
a system. Speech recognition systems are typically trained on thousands
of hours of transcribed audio. In this project, the team was initially
given only 80 hours of conversational speech for each language, and in
each succeeding period a smaller fraction of the audio is transcribed.
At the end of each period, the team will be given a new language to
build a system - initially in four weeks, but by the end of the program
down to just one week.
In addition to Morgan, the leaders of the team are Steven Wegmann of
ICSI, Professor Mari Ostendorf of the University of Washington,
Professor Janet Pierrehumbert of Northwestern University, Professor Eric
Fosler-Lussier of The Ohio State University, and Professor Dan Ellis of
Columbia University. Morgan says an important element of the project is
that these team leaders have had strong previous research ties with one
another in research topics that are essential to the Babel problem.
The project is funded by the Intelligence Advanced Research Projects
Activity (IARPA), a research arm of the Office of the Director of
National Intelligence, which invests in high-risk/high-payoff research
The International Computer Science Institute (ICSI) is a leading center
for research in computer science and one of the few independent,
nonprofit research institutes in the United States. With its unique
focus on international collaboration and its affiliation with the
University of California at Berkeley, ICSI brings together the most
influential U.S. scientists and experts from around the world in areas
such as computer networking and security, speech and language
processing, algorithms, bioinformatics, computer architecture, computer
vision, and artificial intelligence. For more information, check ICSI
out on the Web:
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