ICTACT Journal on Microelectronics

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Design and Analysis of Digital Filters for Speech Signals Using Multirate Signal Processing


Affiliations
1 Department of Electronics and Communication Engineering, PET Engineering College, India
     

   Subscribe/Renew Journal


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.

Keywords

Digital Filters, Sub Band Coding, FIR, IIR, DWT, FFT, FWHT, Quantization, SQNR.
Subscription Login to verify subscription
User
Notifications
Font Size

  • Ankita Mahajan and Rajesh Mehra, “Design Analysis of Word Length Effects in Interpolator Design”, International Journal of Advanced Engineering Research and Technology, Vol. 9, No. 1, pp. 104-108, 2014.

  • Atul Bhargava, “A Survey Report for Design of FIR Filter with Different Method”, International Journal of Science, Engineering and Technology Research, Vol. 2, No. 2, pp. 461-465, 2013.

  • Dolly Agrawal and Divya Kumud, “A Review On Multirate Digital Signal Processing”, International Journal of Electrical and Electronics Engineers, Vol. 6, No. 2, pp. 324-328, 2014.

  • Jagriti Saini and Rajesh Mehra, “Power Spectral Density Analysis of Speech Signal using Window Techniques”, International Journal of Computer Applications, Vol. 131, No. 14, pp. 33-36, 2015.

  • Lalima Singh, “Speech Signal Analysis using FFT and LPC”, International Journal of Advanced Research in Computer Engineering and Technology, Vol. 4, No. 4, pp. 1658-1660, 2015.

  • Lalitha R. Naik and R.L. Devaraja Naik, “Sub-band Coding of Speech Signals using Multirate Signal Processing and Comparing the various parameter of different Speech Signals by Corrupting the same Speech Signal”, International Journal of Emerging Trends and Technology in Computer Science, Vol. 4, No. 2, pp. 217-221, 2015.

  • Prajoy Podder, Tanvir Zaman Khan, Mamdudul Haque Khan and M. Muktadir Rahman, “Comparative Performance Analysis of Hamming, Hanning and Blackman Window”, International Journal of Computer Applications, Vol. 96, No. 18, pp. 1-7, 2014.

  • Rajeev Singh Dohare and Shilpa Datar, “Quantized Coefficient FIR Filter for the design of Filter Bank”, International Journal of Engineering Trends and Technology, Vol. 4, No. 8, pp. 13-18, 2013.

  • Samarjeet Singh and Uma Sharma, “ MATLAB based Digital IIR Filter Design”, International Journal Electronics and Computer Science Engineering, Vol. 1, No. 1, pp. 74-83, 2014.

  • Saurabh Singh Rajput and S.S. Bhadauria, “Implementation of FIR Filter using Efficient Window Function and Its Application In Filtering a Speech Signal”, International Journal of Electrical, Electronic and Mechanical Controls, Vol. 1, No. 2, pp. 158-164, 2012.

  • Suraj R. Gaikwad and Gopal Gawande, “Review: Design of Highly Efficient Multirate Digital Filters”, International Journal of Engineering Research and Applications, Vol. 3, No. 6, pp. 560-564, 2013.

  • Suverna Sengar and Partha Pratim Bhattacharya, ‘Multirate Filtering for Digital Signal Processing and its Applications’, ARPN Journal of Science and Technology, Vol. 2, No. 3, pp. 228-237, 2012.

  • Suraj R. Gaikwad and Gopal S. Gawande, “Implementation of Efficient Multirate Filter Structure for Decimation”, International Journal of Current Engineering and Technology, Vol. 4, No. 2, pp. 1008-1010, 2014.

  • P. Suresh Babu, D. Srinivasulu Reddy and P.V.N. Reddy, “Speech Signal Analysis using Windowing Techniques”, International Journal of Emerging Trends in Engineering Research, Vol. 3, No. 6, pp. 257-263, 2015.

  • Vijayakumar Majjagi, “Sub Band Coding of Speech Signal by using Multi-Rate Signal Processing”, International Journal of Engineering Research and Technology, Vol. 2, No. 9, pp. 45-49, 2013.

  • Vishv Mohan, “Analysis and Synthesis of Speech using Matlab”, International Journal of Advancements in Research and Technology, Vol. 2, No. 5, pp. 373-382, 2013.

  • Vaibhav M Dikhole et al, “Effect of Finite Word Length for FIR Filter Coefficient in Electrocardiogram Filtering”, Proceedings of National Conference on Innovative Trends in Science and Engineering, Vol. 4, No. 7, pp. 266-271, 2016.


Abstract Views: 175

PDF Views: 0




  • Design and Analysis of Digital Filters for Speech Signals Using Multirate Signal Processing

Abstract Views: 175  |  PDF Views: 0

Authors

S. Sangeetha
Department of Electronics and Communication Engineering, PET Engineering College, India
P. Kannan
Department of Electronics and Communication Engineering, PET Engineering College, India

Abstract


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.

Keywords


Digital Filters, Sub Band Coding, FIR, IIR, DWT, FFT, FWHT, Quantization, SQNR.

References