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Introduction to Speech Analysis Project

I – introduction

Signals analysis is commonly applied to voice signals. Voice signals are modulated using Amplitude Modulation (AM) forbroadcast distributions, and signals are compressed before transmission when speaking into a phone. This report will introduce the use of the FourierTransform into speech signals analysis. Specifically, we will attempt to use the Fourier Transform to identify the speaker of a series of words.

To focus our efforts, we present the following problem:

Biometric identification has begun to be used to maintain security. Fingerprint identification door locks are now sold throughcommon stores like Staples (External Link)cmArea=SEARCH . A development team in Spain has created an IRIS scanner that performs person verification to unlock cellular phones using thephone’s built in camera (External Link)&view=frontpage&Itemid=1 . Many biometric identification sensors are expensive, and therefore they have yetto proliferate. A common microphone, though, is very cheap – even cheaper than a camera. This paper investigates the possibility of using voice signals toperform identification.

Specifically, we expect a user to say four numbers from the set “zero” through “nine”. These four numbers are the user’s PersonalIdentification Number (PIN). We will make a comparison of each stated number with previous recordings of that user, and use those comparisons to make adecision as to whether or not there is a match to the user.

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Source:  OpenStax, Analysis of speech signal spectrums using the l2 norm. OpenStax CNX. Dec 12, 2009 Download for free at http://cnx.org/content/col11143/1.2
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