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Questions or comments concerning this laboratory should be directedto Prof. Charles A. Bouman, School of Electrical and Computer Engineering, Purdue University, West Lafayette IN 47907;(765) 494-0340; bouman@ecn.purdue.edu

Introduction

Speech is an acoustic waveform that conveys information from a speaker to a listener. Given the importance of this form of communication, itis no surprise that many applications of signal processing have been developed to manipulate speech signals. Almost all speechprocessing applications currently fall into three broad categories: speech recognition, speech synthesis, and speech coding.

Speech recognition may be concerned with the identification of certain words, or with the identification of the speaker. Isolated word recognition algorithms attempt to identify individual words, such as in automated telephone services.Automatic speech recognition systems attempt to recognize continuous spoken language, possibly to convert into text within a word processor.These systems often incorporate grammatical cues to increase their accuracy. Speaker identification is mostly used in security applications, as a person'svoice is much like a “fingerprint”.

The objective in speech synthesis is to convert a string of text, or a sequence of words, into natural-sounding speech.One example is the Speech Plus synthesizer used by Stephen Hawking (although it unfortunately gives him an American accent).There are also similar systems which read text for the blind. Speech synthesis has also been used to aid scientists in learning about themechanisms of human speech production, and thereby in the treatment of speech-related disorders.

Speech coding is mainly concerned with exploiting certain redundancies of the speech signal, allowing it to be represented in a compressed form.Much of the research in speech compression has been motivated by the need to conserve bandwidth in communication systems.For example, speech coding is used to reduce the bit rate in digital cellular systems.

In this lab, we will describe some elementary properties of speech signals, introduce a tool known as the short-time discrete-time Fourier Transform , and show how it can be used to form a spectrogram . We will then use the spectrogram to estimate properties of speechwaveforms.

This is the first part of a two-week experiment. During thesecond week ,we will study speech models and linear predictive coding.

Time domain analysis of speech signals

The Human Speech Production System

Speech production

Speech consists of acoustic pressure waves created by the voluntary movements of anatomical structures in the human speech productionsystem, shown in [link] . As the diaphragm forces air through the system,these structures are able to generate and shape a wide variety of waveforms. These waveforms can be broadly categorized into voiced and unvoiced speech .

Voiced sounds, vowels for example, are produced by forcing air through the larynx, with the tension of thevocal cords adjusted so that they vibrate in a relaxed oscillation. This produces quasi-periodic pulses of air which are acousticallyfiltered as they propagate through the vocal tract, and possibly through the nasal cavity.The shape of the cavities that comprise the vocal tract, known as the area function , determines the natural frequencies, or formants , which are emphasized in the speech waveform. The period of the excitation, known as the pitch period , is generally small with respect to the rate at which the vocal tract changes shape.Therefore, a segment of voiced speech covering several pitch periods will appear somewhat periodic . Average values for the pitch period are around 8 ms for male speakers,and 4 ms for female speakers.

Questions & Answers

can someone help me with some logarithmic and exponential equations.
Jeffrey Reply
sure. what is your question?
ninjadapaul
20/(×-6^2)
Salomon
okay, so you have 6 raised to the power of 2. what is that part of your answer
ninjadapaul
I don't understand what the A with approx sign and the boxed x mean
ninjadapaul
it think it's written 20/(X-6)^2 so it's 20 divided by X-6 squared
Salomon
I'm not sure why it wrote it the other way
Salomon
I got X =-6
Salomon
ok. so take the square root of both sides, now you have plus or minus the square root of 20= x-6
ninjadapaul
oops. ignore that.
ninjadapaul
so you not have an equal sign anywhere in the original equation?
ninjadapaul
Commplementary angles
Idrissa Reply
hello
Sherica
im all ears I need to learn
Sherica
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Tamia
what is a good calculator for all algebra; would a Casio fx 260 work with all algebra equations? please name the cheapest, thanks.
Kevin Reply
a perfect square v²+2v+_
Dearan Reply
kkk nice
Abdirahman Reply
algebra 2 Inequalities:If equation 2 = 0 it is an open set?
Kim Reply
or infinite solutions?
Kim
The answer is neither. The function, 2 = 0 cannot exist. Hence, the function is undefined.
Al
y=10×
Embra Reply
if |A| not equal to 0 and order of A is n prove that adj (adj A = |A|
Nancy Reply
rolling four fair dice and getting an even number an all four dice
ramon Reply
Kristine 2*2*2=8
Bridget Reply
Differences Between Laspeyres and Paasche Indices
Emedobi Reply
No. 7x -4y is simplified from 4x + (3y + 3x) -7y
Mary Reply
is it 3×y ?
Joan Reply
J, combine like terms 7x-4y
Bridget Reply
im not good at math so would this help me
Rachael Reply
yes
Asali
I'm not good at math so would you help me
Samantha
what is the problem that i will help you to self with?
Asali
how do you translate this in Algebraic Expressions
linda Reply
Need to simplify the expresin. 3/7 (x+y)-1/7 (x-1)=
Crystal Reply
. After 3 months on a diet, Lisa had lost 12% of her original weight. She lost 21 pounds. What was Lisa's original weight?
Chris Reply
what's the easiest and fastest way to the synthesize AgNP?
Damian Reply
China
Cied
types of nano material
abeetha Reply
I start with an easy one. carbon nanotubes woven into a long filament like a string
Porter
many many of nanotubes
Porter
what is the k.e before it land
Yasmin
what is the function of carbon nanotubes?
Cesar
what is nanomaterials​ and their applications of sensors.
Ramkumar Reply
what is nano technology
Sravani Reply
what is system testing?
AMJAD
preparation of nanomaterial
Victor Reply
Yes, Nanotechnology has a very fast field of applications and their is always something new to do with it...
Himanshu Reply
good afternoon madam
AMJAD
what is system testing
AMJAD
what is the application of nanotechnology?
Stotaw
In this morden time nanotechnology used in many field . 1-Electronics-manufacturad IC ,RAM,MRAM,solar panel etc 2-Helth and Medical-Nanomedicine,Drug Dilivery for cancer treatment etc 3- Atomobile -MEMS, Coating on car etc. and may other field for details you can check at Google
Azam
anybody can imagine what will be happen after 100 years from now in nano tech world
Prasenjit
after 100 year this will be not nanotechnology maybe this technology name will be change . maybe aftet 100 year . we work on electron lable practically about its properties and behaviour by the different instruments
Azam
name doesn't matter , whatever it will be change... I'm taking about effect on circumstances of the microscopic world
Prasenjit
how hard could it be to apply nanotechnology against viral infections such HIV or Ebola?
Damian
silver nanoparticles could handle the job?
Damian
not now but maybe in future only AgNP maybe any other nanomaterials
Azam
can nanotechnology change the direction of the face of the world
Prasenjit Reply
At high concentrations (>0.01 M), the relation between absorptivity coefficient and absorbance is no longer linear. This is due to the electrostatic interactions between the quantum dots in close proximity. If the concentration of the solution is high, another effect that is seen is the scattering of light from the large number of quantum dots. This assumption only works at low concentrations of the analyte. Presence of stray light.
Ali Reply
the Beer law works very well for dilute solutions but fails for very high concentrations. why?
bamidele Reply
how did you get the value of 2000N.What calculations are needed to arrive at it
Smarajit Reply
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Source:  OpenStax, Purdue digital signal processing labs (ece 438). OpenStax CNX. Sep 14, 2009 Download for free at http://cnx.org/content/col10593/1.4
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