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About Multichannel Speech Signal Extraction and Separation Techniques
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作者 Adel Hidri Souad Meddeb Hamid Amiri 《Journal of Signal and Information Processing》 2012年第2期238-247,共10页
The extraction of a desired speech signal from a noisy environment has become a challenging issue. In the recent years, the scientific community has particularly focused on multichannel techniques which are dealt with... The extraction of a desired speech signal from a noisy environment has become a challenging issue. In the recent years, the scientific community has particularly focused on multichannel techniques which are dealt with in this review. In fact, this study tries to classify these multichannel techniques into three main ones: Beamforming, Independent Component Analysis (ICA) and Time Frequency (T-F) masking. This paper also highlights their advantages and drawbacks. However these previously mentioned techniques could not afford satisfactory results. This fact leads to the idea that a combination of those techniques, which is depicted along this study, may probably provide more efficient results. Indeed, giving the fact that those approaches are still be considered as being not totally efficient, has led us to review these mentioned above in the hope that further researches will provide this domain with suitable innovations. 展开更多
关键词 BEAMFORMING ICA T-F MASKING BSS MULTICHANNEL Speech Separation MICROPHONE Array
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Image Classification using Statistical Learning Methods
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作者 Jassem Mtimet Hamid Amiri 《Journal of Software Engineering and Applications》 2012年第12期200-203,共4页
In general, digital images can be classified into photographs, textual and mixed documents. This taxonomy is very useful in many applications, such as archiving task. However, there are no effective methods to perform... In general, digital images can be classified into photographs, textual and mixed documents. This taxonomy is very useful in many applications, such as archiving task. However, there are no effective methods to perform this classification automatically. In this paper, we present a method for classifying and archiving document into the following semantic classes: photographs, textual and mixed documents. Our method is based on combining low-level image features, such as mean, Standard deviation, Skewness. Both the Decision Tree and Neuronal Network Classifiers are used for classification task. 展开更多
关键词 IMAGE CLASSIFICATION DECISION TREE NEURONAL Network STATISTICAL analysis
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