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ON CAMPUS
Speaking of security
Voiceprint authentication a la “Star Trek” could be poised
to become reality
by ken chiacchia
Now, what was that password This was the system that
needed eight digits, right Did it require symbols, or just
letters and numbers
Today’s password-driven electronic security systems have
a face only a system security administrator could love.
Better to use some kind of biometric—something
physically a part of us, marking us as ourselves. Some
systems already use fingerprints. What about a voiceprint
Wouldn’t it be great if our computers could recognize us,
the way the Enterprise recognized Captain Kirk saying,
“Zero-zero-zero destruct zero”
Simply recognizing human speech isn’t all that hard
for today’s computers. Take Apple’s voice-activated Siri
assistant, for example. Matching voiceprints is possible,
too, and is already being done by commercially available
software from companies such as Nuance and Auraya.
The problem is making the voiceprints themselves secure
and difficult to steal, says Bhiksha Raj, associate professor
and non-tenured faculty chair at the School of Computer
Science’s Language Technologies Institute. But Raj and his
colleagues may have found the way forward.
“Where (the work) really began was when we realized
that every time we use our voice to authenticate
(ourselves), we put ourselves at risk,” Raj explains.
“Your voice is supposed to be a viable biometric, but
once you’ve given it away it becomes just another bit
of data out there.”
Just as a stolen password can leave your email or financial
data wide open, a cracker could potentially steal your
voiceprint from a database and take over part of your
life, at least as effectively as if he’d stolen your social
security number.
The question that stumped Raj and his colleagues was:
Could they somehow get “Siri” to respond to voice
commands without sending the actual voiceprint over
the network and into the cloud, where it would be
vulnerable to theft
old-school encryption
The obvious answer to the problem was to encrypt the voice
recording. A system would store an encrypted version of
your voice, identifying you without actually having access
to your voice. Each system would have its own encrypted
version, impossible to connect with each other or with your
original voiceprint.
To accomplish this, Raj and his colleagues had to solve two
problems. The first was authentication itself.
“Speech is a noisy signal,” says Shanatu Rane, a principal
research scientist at Mitsubishi Electric Research
Laboratories, who collaborated with Raj on his early
work. “If you say something now, and then say it again five
minutes later, the two signals are not going to be identical.”
There’s simply no way to make a person’s voice input
completely stable in the same way as a typed password.
To solve this issue, the voice authentication process
employed by Raj’s team used Gaussian mixture models,
or GMMs. GMMs are a way to statistically match up a
given pattern to a standard sample. In this case, Raj says,
the researchers used the parameters of the GMMs they
calculated from individual voice recordings to represent
the actual recordings. Using GMMs, their system achieved
excellent results both in terms of recall (the ability to
recognize a matching voice sample) and precision (the
ability to avoid accepting a nonmatching sample).
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