NMT EE 451L - Noise Removal for Audio Files (2 pages)

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Noise Removal for Audio Files



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Noise Removal for Audio Files

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Lecture Notes


Pages:
2
School:
New Mexico Institute of Mining and Technology
Course:
Ee 451l - Digital Signal Processing Lab

Unformatted text preview:

Fall 2009 EE451L Noise Removal for Audio Files Introduction Like any signal audio recordings are very susceptible to noise and interference This noise can come from many sources Dust in the grooves on an LP record causes the needle to jump creating the typical ticks and pops Even if a record is dust free imperfections in the cutting process leave the inside of the track rough creating the characteristic hissing sound of an old record Professional recording studios are designed to eliminate noise Anechoic chambers are used to stifle reflected sounds and eliminate echoes Pop screens over microphones reduce the noise of a person s breath when they speak from close range Real world recordings encounter even more types of noise Fluorescent lights can cause a hum that will barely noticeable to a person but can still be picked up by a microphone and then amplified in the final output No matter what the source of the noise it is often desirable to remove the noise In this project you will be given an audio file that has been corrupted by noise You are to indentify the signal as well as any noise sources that are present Then using the DSP board clean the file and remove the noise Procedure 1 Open the corrupted audio file noise corrupted wav using Windows Media Player and listen to it Can you make out who the voice belongs to and what is being said What other noises do you hear 2 Using MATLAB open the file and determine its Power Spectral Density From the Power Spectral Density attempt to locate and identify the base signal and any noise sources that as present Consider the range of human hearing as well as the typical range for voices The following MATLAB commands may be useful in doing this wavread fft fftshift Be careful when plotting the PSD that the x scale is correct List a description of any signals you detect 3 Using MATLAB design filters to remove the noise What types of filters are needed to remove each noise source Are IIR or FIR filters more appropriate for



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