Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the application of 2-D FFT, Radon transform, the 1-D IFFT,and 1-D discrete wavelet transforms were used in the first proposed model, while discrete multicircularlet transform was used in the second proposed model. The final stage of the proposed models includes the use of the dynamic time warping algorithm for recognition tasks. The performance of the proposed systems was evaluated using forty different isolated Arabic words that are recorded fifteen times in a studio for speaker dependant. The result shows recognition accuracy of (91% and 89%) using discrete wavelet transform type Daubechies (Db1) and (Db4) respectively, and the accuracy score between (87%-93%) was achieved using
discrete multicircularlet transform for 9 sub bands.
In this research, the problem of multi- objective modal transport was formulated with mixed constraints to find the optimal solution. The foggy approach of the Multi-objective Transfer Model (MOTP) was applied. There are three objectives to reduce costs to the minimum cost of transportation, administrative cost and cost of the goods. The linear membership function, the Exponential membership function, and the Hyperbolic membership function. Where the proposed model was used in the General Company for the manufacture of grain to reduce the cost of transport to the minimum and to find the best plan to transfer the product according to the restrictions imposed on the model.
The study aims to biosynthesized of sliver nanoparticle from aqueous extract of olive leave and evaluate the effectiveness of the synthesis AgNPs against isolated fungi. The study mediating fifty samples were taken from various tools in laboratory from five hospitals in Baghdad. Four species of fungi were identified depending on the morphological and microscopic characteristics. The most common isolated fungi based on their frequency ratio were as follows Aspergillus niger 87.5%, Aspergillus flavus 62.5%, Aspergillus fumigatus 53.5% and Aspergillus nidulans 37.7%.The Biosynthesis of silver nanoparticle developed a rapid, eco-friendly and convenient green method for the stable silver nanoparticles (AgNP
... Show MoreIn Algeria, education is compulsory for males and females. This foundational decision was taken right after the independence of the country in 1962. Soon after, in 1963, the central government decided the Arabisation of the whole educational levels starting from primary school till university. At the same period, illiteracy-eradication programmes were launched by the Ministry of Education to get rid of this post-colonial scourge. In the administrative department (or Wilaya) of Adrar, former Tuat, young males and females attend Quranic schools (Zawaya) well before any formal education, that is as early as 4-5 years of age. The adult people who are not enrolled in formal classes could sit for non-formal ones. However, actual measurements a
... Show MoreAs a new technology, blockchain provides the necessary capabilities to assure data integrity and data security through encryption. Mostly, all existing algorithms that provide security rely on the process of discovering a suitable key. Hence, key generation is considered the core of powerful encryption. This paper uses Zernike moment and Mersenne prime numbers to generate strong prime numbers by extracting the features from biometrics (speech). This proposed system sends these unique and strong prime numbers to the RSA algorithm to generate the keys. These keys represent a public address and a private key in a cryptocurrency wallet that is used to encrypt transactions. The benefit of this work is that it provides a high degree
... Show MoreIn any language there is some amount of difference between written language (planned) and spoken language (spontaneous). Since planned speech could be considered a form of written language, it could be inferred that there are also differences between planned speech and spontaneous speech. Some of these differences are very clear in terms of syntax, lexis, phonology and discourse. These differences are highlighted in order to make a clear distinction between spontaneous and planned speech.
This paper is an attempt to show the differences between the two forms of a language (written & spoken English) as far as number of linguistic features are tackle
... Show MoreSubcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and
... Show MoreIn this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N
... Show MoreEmotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
... Show MoreIn his study, the researcher highlighted the most important methods of authorship in the fundamentals of jurisprudence and speech. Fundamentalist rules and extraction and access method; they also distinct from each other that each has special divisions of the subjects of jurisprudence.