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Recently, the incorporation of the research done in biologically inspired systems has shown satisfactory results. A promising research area is the understanding of the human auditory systems and its performance under noisy conditions. Moreover, the incorporation of brain functions (cortical response) as an active part of the auditory system seems a viable alternative to increase the robustness of...
This paper presents the process of Quranic Accent Automatic Identification. Recent feature extraction technique that is used for Quranic verse rule identification/Tajweed include Mel Frequency Cepstral Coefficients (MFCC) which prone to additive noise and may reduce the classification result. Therefore, to improve the performance of MFCC with addition of Spectral Centroid features and is proposed...
Identification of voice disorders has been a vital role in our life nowadays. Acoustic analysis can be useful tool to diagnose voice disorders as a complementary technique to other medicine methods such as Laryngoscopy and Stroboscopy. In this paper, we scrutinized feature reduction techniques such as principal component analysis (PCA) and linear discriminant analysis (LDA) as feature subset extraction...
This paper presents two nonlinear feature dimensionality reduction methods based on neural networks for a HMM-based phone recognition system. The neural networks are trained as feature classifiers to reduce feature dimensionality as well as maximize discrimination among speech features. The outputs of different network layers are used for obtaining transformed features. Moreover, the training of the...
In this paper, we presented the corpus collection procedure and proposed the effective feature representation. We collected the emotional speech from 50 male and 50 female speakers and the corresponding statistics of the corpus was also demonstrated. The emotional speech corpus was further processed manually for the feature extraction and classification experiments. After introducing the feature generation...
Audio event detection is one of the tasks of the European project VIDIVIDEO. This paper focuses on the detection of non-speech events, and as such only searches for events in audio segments that have been previously classified as non-speech. Preliminary experiments with a small corpus of sound effects have shown the potential of this type of corpus for training purposes. This paper describes our experiments...
Support vector machines (SVMs) have been applied in speaker verification successfully. But they cannot easily deal with the dynamic time structure of audio data, since they are constrained to work with fixed-length vectors. In this paper, we propose a new feature extraction approach based on PCA and improved Fisher score for the sake of solving this problem existed in SVM. This new feature extraction...
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