Speech Coding Based on Orthogonal and Biorthogonal Wavelet

Joseph, Shijo M.; Anto, Puji

doi:10.1016/j.protcy.2012.10.047

Cited by 5 publications

(2 citation statements)

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“…For high-frequency coefficients, no analysis is performed any further. The approximation signal is then classified into new approximation and detailed signals [18]. The bi-orthogonal (9/7) wavelet decomposition is performed using [19,20]: Equations (2)-(5) for "lifting" phase: 6), (7) for "scaling" phase:…”

Section: Bi-orthogonal (Tap 9/7) Wavelet Transformmentioning

confidence: 99%

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Audio compression using transforms and high order entropy encoding

Ahmed

George

Hadi

2021

IJECE

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<span>Digital audio is required to transmit large sizes of audio information through the most common communication systems; in turn this leads to more challenges in both storage and archieving. In this paper, an efficient audio compressive scheme is proposed, it depends on combined transform coding scheme; it is consist of i) bi-orthogonal (tab 9/7) wavelet transform to decompose the audio signal into low & multi high sub-bands, ii) then the produced sub-bands passed through DCT to de-correlate the signal, iii) the product of the combined transform stage is passed through progressive hierarchical quantization, then traditional run-length encoding (RLE), iv) and finally LZW coding to generate the output mate bitstream. The measures Peak signal-to-noise ratio (PSNR) and compression ratio (CR) were used to conduct a comparative analysis for the performance of the whole system. Many audio test samples were utilized to test the performance behavior; the used samples have various sizes and vary in features. The simulation results appear the efficiency of these combined transforms when using LZW within the domain of data compression. The compression results are encouraging and show a remarkable reduction in audio file size with good fidelity.</span>

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Section: Bi-orthogonal (Tap 9/7) Wavelet Transformmentioning

confidence: 99%

“…Discrete cosine transform, first submitted by [18] in 1974, has become very significant in recent years. DCT has many performed because of its optimal accomplishment, it applied in the signal, image analysis, and applied especially in speech compression because of its optimal achievement.…”

Section: Discrete Cosine Transform (Dct)mentioning

confidence: 99%