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	Research on the effectiveness of noise reduction when encoding a lossless speech signal</div>

Tamilselvan Akilan, Raja Laxmi , Udhayakumar Hariharan

2022 , VOLUME 22, NUMBER 2 ( March-April )

ISSN 2226-1494 (print), ISSN 2500-0373 (online)

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Nikiforov
Vladimir O.
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doi: 10.17586/2226-1494-2022-22-2-254-261

Research on the effectiveness of noise reduction when encoding a lossless speech signal

T. Akilan, L. Raja, U. Hariharan

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Akilan T., Raja L., Hariharan U. Research on the effectiveness of noise reduction when encoding a lossless speech signal. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2022, vol. 22, no. 2, pp. 254–261. doi: 10.17586/2226-1494-2022-22-2-254-261

Abstract

In the meantime, speech coding is one of the methods to represent the digital speech signal as in possible fewer bits value and to maintain the quality and its clearness. In omnipresent situations, encryption and examination of speech maintain a crucial role in various acoustic-based coding systems. This paper, using subband and Huffman coding technique, has been used for speech signals description to reduce the occupied by the speech data memory. The amplitude values of the taken speech are segregated after pre-processing, windowing and decomposition techniques. These data are converted into the frequency domain using discrete cosine transform (DCT). Then 90 foremost coefficients have been coded by Huffman method, they contain the most valuable information of speech signals. Signals are segregated then and subband coding techniques applied. To reconstruct the input speech, the taken speech is re-transformed in the form of time-domain applying through inverse discrete cosine transform (IDCT). This experiment is carried out by speech data at 8 kHz with 16 bits/per sample. The SNR (Signal to Noise Ratio) shows the efficiency of this applied technique.

Keywords: decomposition, IDCT, DCT, Huffman, SNR, subband, quantization, windowing

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