Filter Implementation Using Dsp Kit

8/3/2019 Filter Implementation Using Dsp Kit

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Guided by: Pro. Tanish ZaveriPravin Gondaliya(08BEC029)

Surendra Jalu(08BEC029)


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Goal

To understand the model of speech generation inhuman beings.

To understand speech enhancement techniques.

To explore the features and peripherals of theSpartan III DSP kit.

Implement a low pass filter using VHDL coding.

Filter the speech signal on FPGA kit in real time.


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Scopes of Acoustic Science


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Speech enhancement is concerned with

improving some perceptual aspect of speech that

has been degraded by additive noise. Different kind of noise affect on the quality of the

speech. Different speech enhancement

techniques are used to improve the quality of

speech and reduce the specific noise coming from

different sources at different SNRs.

Speech Enhancement


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Speech enhancement has three major goals:

To improve the quality and intelligibility of speechcorrupted by background noise. To make speech coders robust when to input noise. To make speech recognition systems more robust

to input noise.

Goals and Classes of SpeechEnhancement


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Speech enhancement techniques are divided in mainthree classes.

Statistical model based algorithmsWiener a priori SNR methodWavelet thresholding method

Log MMSE estimator method

Spectral subtractive algorithmsSpectral subtraction algorithmMultiband spectral subtractive algorithm

Subspace algorithms

Cont


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Wavelet-based speech enhancement algorithm canbe summarized by the following three steps :

Wavelet transform of noisy signal Thresholding the resulting wavelet coefficients

Inverse transform to obtain the denoised signal

Hard thresholding , Soft thresholding, Non linearthresholding

Wavelet Thresholding Method


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It is one of the most popular methods of reducing theeffect of background (additive) noise. Assume that y(n),noise corrupted input signal is composed of the clean

speech signal x(n) and additive noise signal d(n) :y(n) = x(n) + d(n)Taking Discrete Fourier Transform on both sides

Y () = X() + D()

Y() in polar form :Y() = |Y()| exp(jy())|Y()| is the magnitude and exp(jy()) is the phasespectrum of the corrupted noisy signal.

Spectral Subtraction Method


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Block Diagram


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Noise signal does not affect the speech signal uniformlyover the whole spectrum. Some frequencies are affectedmore adversely than the others depending on the

spectral characteristics of the noise..So in MBSS Speech is processed into N (1 N 8)overlapping frequency bands and spectral subtraction isperformed independently on each band using band-

specific over-subtraction factors . This method providesa greater degree of flexibility and control on the noisesubtraction levels that reduces artifacts in the enhancedspeech, resulting in improved speech quality.

Multi Band Spectral

Subtraction(MBSS) Method


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The Spartan 3A DSP reference kit is an integratedcircuit development platform for Xilinxs Spartan

3A DSP FPGA. 189Kbytes of block RAM, Digital clock

management.

The reference board also features external non

volatile memory (SPI flash) and volatile (DDRSDRAM) memory, power supplies, LCD ports,

Audio, Camera, Video Interfaces and other I/Odevices.

Introduction of kit


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FPGA Configuration Options

1) SPI Serial Flash

2) JTAG Buttons and Switches

8 position DIP switch

8 Discrete LEDs

One push button Switch

Push Button Switch to initiate FPGA programming.

Cont


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Generate VHDL code using matlab FDA tool.

Create a project in ISE project navigator and add

VHDL file to project. Synthesize and implement the file.

Generate bit file for loading into the kit.

Load bit file using iMPACT.

Test the results.

Design steps


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Give speech input to one of the stereo channel andnoise tone to other channel. These two signals will beadded together and generate a noisy speech.

This speech will be filtered by suitable low pass filterand given to the speaker.

Design


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THANKYOU

Filter Implementation Using Dsp Kit

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