[sudo-discuss] Breaking: Oakland to lead country in, diverting anti-terror funding to ubiquitous warrantless surveillance

[Anthony Di Franco]

I just came across this Bruce Schneier talk about the big-picture issues of
increasingly powerful technology for communication / surveillance and found
it to be relevant to the discussion here:
https://www.youtube.com/watch?v=h0d_QDgl3gI


On Thu, Oct 17, 2013 at 10:27 AM, Patrik D'haeseleer <patrikd at gmail.com>wrote:

> On Thu, Oct 17, 2013 at 6:41 AM, GtwoG PublicOhOne <g2g-public01 at att.net>wrote:
>
>> And voiceprint attribution was 99.96% accurate as of 1962
>> (published); fast-forward at the speed of Moore's law, draw your own
>> conclusions, and more details in person.
>>
>
> Note that the accuracy of voiceprint identification has been hugely
> exaggerated. That number has been touted primarily by prosecutors, and by
> voiceprint identification "experts" who make a nice buck from offering
> their services. But just as has been the case with lie detectors, these
> claims have not stood up to rigorous scientific validation.
>
> Of course, that doesn't mean that they won't be used against you in a
> court of law, regardless of your guilt or innocence! And some people<http://www.innocenceproject.org/Content/David_Shawn_Pope.php>have been falsely convicted to decades in jail or worse on the basis of
> this kind of "evidence".
>
>
> http://sourcesandmethods.blogspot.com/2013/08/is-forensic-speaker-recognition-next.html
>  Forensic speaker recognition has many limitations and is currently
> inadmissible in federal court as expert testimony. Bonastre et al (2003)
> summarize these limitations quite well:
>
> "The term *voiceprint* gives the false impression that voice has
> characteristics that are as unique and reliable as fingerprints... this is
> absolutely not the case."
>
> The thing about voices is that they are susceptible to a myriad of
> external factors such as psychological/emotional state, age, health,
> weather... the list goes on. From an application standpoint, the most
> prominent of these factors is intentional vocal disguise. There are a
> number of things people can intentionally do to their voices to drastically
> reduce the ability of machine or human expert to identify their voice
> correctly (you would be amazed at how difficult it is - nearly impossible -
> to identify a whispered voice). Under these conditions, identification
> accuracy falls to 40 - 52 percent (Thompson 1987), 36 percent (Andruski
> 2007), 26 percent (Clifford 1980).
>
> Patrik
>
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