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Audio Compression Based on Discrete Cosine Transform, Run ...
http://www.ijeit.com/Vol%204/Issue%201/IJEIT1412201407_08.pdf#:~:text=The%20most%20common%20characteristic%20of%20audio%20signals%20is,the%20format%20of%20quantized%20coefficients%20values%20using%20one
Audio Compression - an overview | ScienceDirect Topics
https://www.sciencedirect.com/topics/computer-science/audio-compression
Stereo redundancy coding. The MPEG/ audio compression algorithm supports two types of stereo redundancy coding: intensity stereo coding and middle/side (MS) stereo coding. All layers support intensity stereo coding.
Redundancy Remove Technique for Real Time Voice …
http://www.iosrjen.org/Papers/vol5_issue2%20(part-4)/F5242832.pdf
final receiver exposed to this signal (the listener).Redundancy reduction processes have proven highly effective in compressing the bandwidth of voice signal. Audio compression algorithms are often referred to as “audio encoders”. Applications reduces required storage space as well as reduces required transmission bandwidth.
Compression of Audio Using Transform Coding
http://www.jocm.us/uploadfile/2019/0308/20190308035942448.pdf
speech/audio compression systems is to reduce the number of bits needed to represent an audio signal with the aim of minimizing memory storage costs and transmission bandwidth requirements. The basic way of audio compression is depend on removing signal redundancy while preserving the clearness of the signal [5]. The most popular audio coders are depending …
Audio Compression Based on Discrete Cosine Transform, Run ...
http://www.ijeit.com/Vol%204/Issue%201/IJEIT1412201407_08.pdf
Abstract— Audio compression addresses the problem of reducing the amount of data required to represent digital audio. It is used for reducing the redundancy by avoiding the unnecessary duplicate data. In the present work a low complexity and efficient coding scheme based on discrete cosine transform (DCT) is proposed.
Lossless Compression ofAudio Data
https://www.montana.edu/rmaher/publications/maher_lossless_chapter_2003.pdf
an audio signal consisting ofwhite noise would thwart any attempt at redundancy removal. Thus, we must be prepared to accept results in which the bit rate ofthe losslessly compressed data is not significantly reduced compared to the original rate. Because most audio signals of interest have temporal and spectral properties that vary with
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