Robots to replace Linguistic Anthropologists

Kerim Friedman oxusnet at GMAIL.COM
Tue Oct 28 05:36:57 UTC 2008


I, for one, welcome our new robotic converstational analysis overlords.

- Kerim

http://www.nytimes.com/2008/10/26/business/26novelties.html

October 26, 2008
Novelties
You May Soon Know if You're Hogging the Discussion
By ANNE EISENBERG

PEOPLE who want to improve their communication skills may one day have
an unusual helper: software programs that analyze the tone,
turn-taking behavior and other qualities of a conversation. The
programs would then tell the speakers whether they tend to interrupt
others, for example, or whether they dominate meetings with
monologues, or appear inattentive when others are talking.

The inventor of this technology is Alex Pentland of the Massachusetts
Institute of Technology, who has developed cellphone-like gadgets to
listen to people as they chat, and computer programs that sift through
these conversational cadences, studying communication signals that lie
beneath the words.

If commercialized, such tools could help users better handle many
subtleties of face-to-face and group interactions — or at least stop
hogging the show at committee meetings.

With the help of his students, Dr. Pentland, a professor of media arts
and sciences at M.I.T., has been equipping people in banks,
universities and other places with customized smartphones or thin
badges packed with sensors that they wear for days or even months. As
these people talk with one another, the sensors collect data on the
timing, energy and variability of their speech.

Dr. Pentland, known as Sandy, calls his gleaning and processing of
conversational and other data "reality mining — using data mining
algorithms to parse the real life, analog world of social
interactions."

The tools he has developed might help people change their
communication tactics, including those that lead to unproductive
workplace dynamics, said David Lazer, an associate professor of public
policy at the Kennedy School of Government at Harvard.

Mr. Lazer praised "the richness of the data" captured by the process —
the "minute-by-minute, fine-grained data on whether you are talking,
whom you prefer to talk with, what your tone is, and if you interrupt,
for instance."

That kind of tool is rare, Mr. Lazer said. "Our existing research
tools for gathering this kind of data aren't very good," he said — for
example, questionnaires in which people self-report on conversations.
Reality mining may be more accurate, and has the potential to show
"all sorts of interactive patterns that may not be obvious to
individuals in an organization," he said.

Many of Dr. Pentland's research studies with smartphones and badges
with embedded sensors are discussed in his new book, "Honest Signals,"
recently published by MIT Press. The badges use tools including
infrared sensors to tell when people are facing one another,
accelerometers to record gestures, and microphones and audio
signal-processing to capture the tone of voice.

With the array of sensors, the badges can detect what Dr. Pentland
calls "honest signals, unconscious face-to-face signaling behavior"
that suggest, for example, when people are active, energetic followers
of what other people are saying, and when they are not. He argues that
these underlying signals are often as important in communication as
words and logic.

For example, the badges register when listeners respond with regular
nods or short acknowledgments like, "Right." Such responses, he
argues, are a kind of mirroring behavior that may help build empathy
between speaker and listener. He also examines patterns of turn-taking
in conversations, as well as gestures and other, often unconscious
signals.

Future smartphones that take advantage of his technology may act as
friendly personal assistants, automatically putting through calls from
friends and family, but sending all others straight through to voice
mail.

"The phone can be like a butler who really gets to know you," he said,
by deciding to ring brightly for an urgent call when its owner has
forgotten to turn on the ringer.

In the research, many steps are taken to make sure the identities of
participants remain anonymous, said Anmol Madan, a graduate student of
Dr. Pentland. For instance, when microphone audio data is collected,
the microphone picks up tone and the length of speaking time but does
not record any of the actual words spoken.

So far, Mr. Madan has found that the data gathered by mobile phones is
far more accurate than accounts of the same information reported by
participants.

"Humans have a lot of bias when they recall their behavior," he said.

Tanzeem Choudhury, a former student and collaborator of Dr. Pentland
and now an assistant professor of computer science at Dartmouth,
continues to do reality mining with smartphones.

"We spend a lot of time talking about how to improve communication
skills," she said. "This work lets us pin down what makes
conversations effective by analyzing people's actual conversation in
their social networks."



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