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DESIGN AND ANALYSIS OF DIGITAL FILTERS FOR SPEECH SIGNALS USING MULTIRATE SIGNAL PROCESSING

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Digital filters provide an important role in the world of communication. This paper proposes the design of digital filters for audio application using multi rate signal processing. One of the important applications in multi rate signal processing is sub band coding. The main objective of this paper is to analyze various techniques for designing digital filters for speech signals. Additive White Gaussian Noise is added with the input speech signal. The input speech signal spectrum is divided into frequency sub-bands using down sampling by a factor 2. Various transforms like FFT, FWHT and DWT are applied to the signal and its sub bands. Then the low pass and high pass FIR filters are designed and implemented using windowing techniques and IIR filters are designed and implemented using Butterworth and Chebyshev filters. Finally quantization is performed on the filter coefficients of signal and its sub bands. The performances of digital filters are measured by calculating Signal to Quantization Noise Ratio. From the performance measures this paper concludes that, which filtering technique is most suitable for designing digital filters for speech signals.
Title: DESIGN AND ANALYSIS OF DIGITAL FILTERS FOR SPEECH SIGNALS USING MULTIRATE SIGNAL PROCESSING
Description:
Digital filters provide an important role in the world of communication.
This paper proposes the design of digital filters for audio application using multi rate signal processing.
One of the important applications in multi rate signal processing is sub band coding.
The main objective of this paper is to analyze various techniques for designing digital filters for speech signals.
Additive White Gaussian Noise is added with the input speech signal.
The input speech signal spectrum is divided into frequency sub-bands using down sampling by a factor 2.
Various transforms like FFT, FWHT and DWT are applied to the signal and its sub bands.
Then the low pass and high pass FIR filters are designed and implemented using windowing techniques and IIR filters are designed and implemented using Butterworth and Chebyshev filters.
Finally quantization is performed on the filter coefficients of signal and its sub bands.
The performances of digital filters are measured by calculating Signal to Quantization Noise Ratio.
From the performance measures this paper concludes that, which filtering technique is most suitable for designing digital filters for speech signals.

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