Digital Signal Processing

S. Abd El-Moneim ¹, M. A. Nassar ², M. Abdelnaby ², F. E. Abd El-Samie ³

Affiliations
1 Department of Electronics and Electrical Communications, Faculty of Electronic Engineering. Menoufia University, Menouf, 32952, EG
2 Department of Electronics and Electrical Communications, Faculty of Electronic Engineering. Menoufia University, Menouf, 32952, EG
3 Department of Electronics and Electrical Communications, Menoufia University, Menouf, 32952, EG

Abstract

Speech signal is a signal that conveys information about the identity, words, age and emotional state of the speaker. If this signal is corrupted by noise, this information may be lost or become difficult to hear.There are several speech enhancement methods such as spectral subtraction method, Wiener filter method and adaptive wiener filtering method. A proposed method of speech enhancement to reduce the degradation of speech signal is introduced in this paper depending on speech averaging, median filtering or minimum periodogram. This averaging method can be used as a preprocessing step in speaker identification. Simulation results show a good performance of the proposed speech enhancement method.

Keywords

Speech Recognition, Speech Enhancement, Speech Averaging, Spectral Subtraction,Wiener Filter, Adaptive Wiener Filter, Speech Quality Metrics.

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Hala Shawky ¹, A. Nassar ², M. Abdelnaby ², F. E. Abd El-Samie ³

Affiliations
1 Department of Electronics and Electrical Communication, Menouf University, Menouf, IN
2 Department of Electronics and Electrical Communication, Menouf University, Menouf, EG
3 Department of Electronics and Electrical Communication, Menouf University, Menouf, EG

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.

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Mohamed M. Al-Abasy ¹, M. I. Dessouky ², M. Abdelnaby ³, F. E. Abd El-Samie ²

Affiliations
1 Department of Electronics and Electrical Communications, Menoufia University, Menouf, 32952, EG
2 Department of Electronics and Electrical Communications, Menoufia University, Menouf, 32952, EG
3 Department of Electronics and Electrical Communications, Menoufia University, Menouf, 32952, EG

Abstract

The importance of seismic wave researches concentrate of the ability to predict earthquake and also obtain information on the Earth’s composition and features. Compression is the reduction of signal size to save storage capacity, transmission time, and cost. In this paper, we propose a technique for seismic signal compression and two techniques for seismic signal reconstruction. Compression is performed with a decimation process, which reduces the sampling rate. The reconstruction of the original seismic signal can be performed using inverse interpolation techniques such as maximum entropy and regularization theory. In addition, we apply compression through multiplication of a certain non-square matrix followed by a pseudo-inverse process for reconstruction. Finally we assess the quality of the reconstructed signals using quality measures such as Signal-to-Noise Ratio (SNR), segmental Signal-to-Noise Ratio (SNRseg), Spectral Distortion (SD), and Log-Likelihood Ratio (LLR).

Keywords

Seismic Signal, Decimation, Maximum Entropy, Regularization Theory.

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