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Speech Signal Compression and Reconstruction Using Inverse Technique


Affiliations
1 Department of Electronics and Electrical Communication, Menouf University, Menouf, India
2 Department of Electronics and Electrical Communication, Menouf University, Menouf, Egypt
3 Department of Electronics and Electrical Communication, Menouf University, Menouf, Egypt
     

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Speech compression is a process of compressing speech signal to reduce its size for transfer. This paper proposed a new technique to compress the speech signal. This technique is called the decimation process. It is opposite of interpolation. This process reduces the sampling rate and thus save time, storage capacity, and cost. Decimation contains two stages, processes of lowpass filtering followed by downsampling. The benefit of using a filter is to avoid aliasing effect. The reconstruction of the original speech signal can be performed using inverse interpolation techniques such as maximum entropy and regularization theory. Finally, we assess the quality of the reconstructed signal using quality metrics such as signal-to-noise ratio (SNR), signal to noise ratio segmental (SNRseg), spectral distortion (SD) and log-likelihood ratio (LLR).

Keywords

Decimation, Interpolation, Maximum Entropy, Regularisation Theory.
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  • Speech Signal Compression and Reconstruction Using Inverse Technique

Abstract Views: 181  |  PDF Views: 1

Authors

Hala Shawky
Department of Electronics and Electrical Communication, Menouf University, Menouf, India
A. Nassar
Department of Electronics and Electrical Communication, Menouf University, Menouf, Egypt
M. Abdelnaby
Department of Electronics and Electrical Communication, Menouf University, Menouf, Egypt
F. E. Abd El-Samie
Department of Electronics and Electrical Communication, Menouf University, Menouf, Egypt

Abstract


Speech compression is a process of compressing speech signal to reduce its size for transfer. This paper proposed a new technique to compress the speech signal. This technique is called the decimation process. It is opposite of interpolation. This process reduces the sampling rate and thus save time, storage capacity, and cost. Decimation contains two stages, processes of lowpass filtering followed by downsampling. The benefit of using a filter is to avoid aliasing effect. The reconstruction of the original speech signal can be performed using inverse interpolation techniques such as maximum entropy and regularization theory. Finally, we assess the quality of the reconstructed signal using quality metrics such as signal-to-noise ratio (SNR), signal to noise ratio segmental (SNRseg), spectral distortion (SD) and log-likelihood ratio (LLR).

Keywords


Decimation, Interpolation, Maximum Entropy, Regularisation Theory.