These and other classified documents provided by former NSA contractor Edward Snowden reveal that the NSA has developed technology not just to record and transcribe private conversations but to automatically identify the speakers.
Americans most regularly encounter this technology, known as speaker recognition, or speaker identification, when they wake up Amazon’s Alexa or call their bank. But a decade before voice commands like “Hello Siri” and “OK Google” became common household phrases, the NSA was using speaker recognition to monitor terrorists, politicians, drug lords, spies, and even agency employees.
The technology works by analyzing the physical and behavioral features that make each person’s voice distinctive, such as the pitch, shape of the mouth, and length of the larynx. An algorithm then creates a dynamic computer model of the individual’s vocal characteristics. This is what’s popularly referred to as a “voiceprint.” The entire process — capturing a few spoken words, turning those words into a voiceprint, and comparing that representation to other “voiceprints” already stored in the database — can happen almost instantaneously. Although the NSA is known to rely on finger and face prints to identify targets, voiceprints, according to a 2008 agency document, are “where NSA reigns supreme.”
It’s not difficult to see why. By intercepting and recording millions of overseas telephone conversations, video teleconferences, and internet calls — in addition to capturing, with or without warrants, the domestic conversations of Americans — the NSA has built an unrivaled collection of distinct voices. Documents from the Snowden archive reveal that analysts fed some of these recordings to speaker recognition algorithms that could connect individuals to their past utterances, even when they had used unknown phone numbers, secret code words, or multiple languages.
Gonzalo San Gil, PhD. on 11 Aug 15"Contents 1 Studies 1.1 Evaluation of the effects of the HADOPI law 1.1.1 University of Delaware and Université de Rennes - 2014 - Graduated Response Policy and the Behavior of Digital Pirates: Evidence from the French Three-Strike (Hadopi) Law 1.1.2 M@rsouin - 2010 - Evaluation of the effects of the HADOPI law (FR) 1.2 People who share files are people who spend the more for culture 1.2.1 Munich School of Management and Copenhagen Business School - Piracy and Movie Revenues: Evidence from Megaupload 1.2.2 The American Assembly (Collumbia University) - Copy Culture in the USA and Germany 1.2.3 GFK (Society for Consumer Research) - Disappointed commissioner suppresses study showing pirates are cinema's best consumers 1.2.4 HADOPI - 2011 - January 2011 study on online cultural practices (FR) 1.2.5 University of Amsterdam - 2010 - Economic and cultural effects of unlawful file sharing 1.2.6 BBC - 2009 - "Pirates" spend more on music (FR) 1.2.7 IPSOS Germany - 2009 - Filesharers are better "consumers" of culture (FR) 1.2.8 Frank N. Magid Associates, Inc. - 2009 - P2P / Best consumers for Hollywood (EN) 1.2.9 Business School of Norway - 2009 - Those who share music spend ten times more money on music (NO) 1.2.10 Annelies Huygen, et al. (Dutch government investigation) - 2009 - Ups and downs - Economische en culturele gevolgen van file sharing voor muziek, film en games 1.2.11 M@rsouin - 2008 - P2P / buy more DVDs (FR) 1.2.12 Canadian Department of Industry - 2007 - P2P / achètent plus de musique (FR) 1.2.13 Felix Oberholzer-Gee (above) and Koleman Strumpf - 2004 -File sharing may boost CD sales 1.3 Economical effects of filesharing 1.3.1 University of Kansas School of Business - Using Markets to Measure the Impact of File Sharing o
