IIR FILTER ARCHITECTURES FOR NOISY NARROWBAND SPEECH ENHANCEMENT: COMPARING BUTTERWORTH, CHEBYSHEV TYPE I, AND ELLIPTIC DESIGNS
DOI:
https://doi.org/10.5281/zenodo.20390049Ключевые слова:
IIR filter, speech enhancement, Butterworth, Chebyshev Type I, Elliptic filter, telephony, narrowband audio, group delayАннотация
Narrowband speech signals occupying the 300–3400 Hz telephony band are routinely degraded by 50/60 Hz power-supply hum, additive white Gaussian noise (AWGN), and high-frequency microphone hiss. While finite impulse response (FIR) filters are preferred for ECG processing due to their linear-phase property, infinite impulse response (IIR) filters offer substantially lower computational order for equivalent stopband attenuation — a critical advantage in real-time voice processing on resource-constrained devices such as VoIP gateways, hearing aids, and mobile telephony chips. This paper presents a MATLAB-based comparative study of three IIR bandpass filter designs — Butterworth (N = 6), Chebyshev Type I (N = 5), and Elliptic/Cauer (N = 4) — evaluated against a synthetic voiced speech signal contaminated with multi-source noise at SNR in = 8 dB. Performance is assessed via output SNR, ∆SNR, MSE, and group delay variation. Spectrogram analysis and pole-zero diagrams complement the quantitative metrics. Results show that the Elliptic filter achieves the highest ∆SNR (11.7 dB) with the lowest pole count (8) and sharpest transition rolloff, at the cost of nonlinear group delay that must be managed in perceptually sensitive applications. Complete MATLAB source code is provided for full reproducibility.Библиографические ссылки
International Telecommunication Union. (1988). ITU-T Recommendation G.711: Pulse Code Modulation (PCM) of Voice Frequencies. ITU-T. https://www.itu.int/rec/T-REC-G.711
Loizou, P. C. (2013). Speech Enhancement: Theory and Practice (2nd ed.). CRC Press. ISBN
-1-4665-0421-9.
Lapsley Miller, J. A., Marshall, L., Heller, L. M., & Hughes, L. F. (2004). Low-level otoacoustic emissions may predict susceptibility to noise-induced hearing loss. Journal of the Acoustical Society of America, 116(1), 223–232. https://doi.org/10.1121/1.1748971
Golomb, B., Kuo, A., Sang, A., & Duda, R. (1998). Effects of nonlinear phase on intelligibility of telephony speech. Proceedings of ICASSP 1998, Seattle, WA. https://doi.org/10.1109/ICASSP.1998.675427
Proakis, J. G., & Manolakis, D. G. (2007). Digital Signal Processing: Principles, Algorithms, and Applications (4th ed.). Pearson Prentice Hall. ISBN 978-0-13-187374-2.
Zverev, A. I. (2005). Handbook of Filter Synthesis. Wiley-IEEE Press. ISBN 978-0-471-74942-5.
Oppenheim, A. V., & Schafer, R. W. (2010). Discrete-Time Signal Processing (3rd ed.). Pearson. ISBN 978-0-13-198842-2.
Hu, Y., & Loizou, P. C. (2007). Evaluation of objective quality measures for speech enhancement. IEEE Transactions on Audio, Speech, and Language Processing, 16(1), 229–238. https://doi.org/10.1109/TASL.2007.911054
Antoniou, A. (2005). Digital Signal Processing: Signals, Systems, and Filters. McGraw-Hill. ISBN
-0-07-145424-5.
Kaiser, J. F. (1966). Digital filters. In F. F. Kuo & J. F. Kaiser (Eds.), System Analysis by Digital Computer. Wiley. Chap. 7.
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