Search results for: sign language recognition
1484 Mistranslation in Cross Cultural Communication: A Discourse Analysis on Former President Bush’s Speech in 2001
Authors: Lowai Abed
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The differences in languages play a big role in cross-cultural communication. If meanings are not translated accurately, the risk can be crucial not only on an interpersonal level, but also on the international and political levels. The use of metaphorical language by politicians can cause great confusion, often leading to statements being misconstrued. In these situations, it is the translators who struggle to put forward the intended meaning with clarity and this makes translation an important field to study and analyze when it comes to cross-cultural communication. Owing to the growing importance of language and the power of translation in politics, this research analyzes part of President Bush’s speech in 2001 in which he used the word “Crusade” which caused his statement to be misconstrued. The research uses a discourse analysis of cross-cultural communication literature which provides answers supported by historical, linguistic, and communicative perspectives. The first finding indicates that the word ‘crusade’ carries different meaning and significance in the narratives of the Western world when compared to the Middle East. The second one is that, linguistically, maintaining cultural meanings through translation is quite difficult and challenging. Third, when it comes to the cross-cultural communication perspective, the common and frequent usage of literal translation is a sign of poor strategies being followed in translation training. Based on the example of Bush’s speech, this paper hopes to highlight the weak practices in translation in cross-cultural communication which are still commonly used across the world. Translation studies have to take issues such as this seriously and attempt to find a solution. In every language, there are words and phrases that have cultural, historical and social meanings that are woven into the language. Literal translation is not the solution for this problem because that strategy is unable to convey these meanings in the target language.
Keywords: Crusade, metaphor, mistranslation, war in terror.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8491483 An Experimental Comparison of Unsupervised Learning Techniques for Face Recognition
Authors: Dinesh Kumar, C.S. Rai, Shakti Kumar
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Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal Component Analysis (PCA), Self Organizing Maps (SOM) and Independent Component Analysis (ICA) are the three techniques among many others as proposed by different researchers for Face Recognition, known as the unsupervised techniques. This paper proposes integration of the two techniques, SOM and PCA, for dimensionality reduction and feature selection. Simulation results show that, though, the individual techniques SOM and PCA itself give excellent performance but the combination of these two can also be utilized for face recognition. Experimental results also indicate that for the given face database and the classifier used, SOM performs better as compared to other unsupervised learning techniques. A comparison of two proposed methodologies of SOM, Local and Global processing, shows the superiority of the later but at the cost of more computational time.
Keywords: Face Recognition, Principal Component Analysis, Self Organizing Maps, Independent Component Analysis
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18801482 Multi-View Neural Network Based Gait Recognition
Authors: Saeid Fazli, Hadis Askarifar, Maryam Sheikh Shoaie
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Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk [1]. Gait recognition has 3 steps. The first step is preprocessing, the second step is feature extraction and the third one is classification. This paper focuses on the classification step that is essential to increase the CCR (Correct Classification Rate). Multilayer Perceptron (MLP) is used in this work. Neural Networks imitate the human brain to perform intelligent tasks [3].They can represent complicated relationships between input and output and acquire knowledge about these relationships directly from the data [2]. In this paper we apply MLP NN for 11 views in our database and compare the CCR values for these views. Experiments are performed with the NLPR databases, and the effectiveness of the proposed method for gait recognition is demonstrated.Keywords: Human motion analysis, biometrics, gait recognition, principal component analysis, MLP neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21051481 Segmentation Free Nastalique Urdu OCR
Authors: Sobia T. Javed, Sarmad Hussain, Ameera Maqbool, Samia Asloob, Sehrish Jamil, Huma Moin
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The electronically available Urdu data is in image form which is very difficult to process. Printed Urdu data is the root cause of problem. So for the rapid progress of Urdu language we need an OCR systems, which can help us to make Urdu data available for the common person. Research has been carried out for years to automata Arabic and Urdu script. But the biggest hurdle in the development of Urdu OCR is the challenge to recognize Nastalique Script which is taken as standard for writing Urdu language. Nastalique script is written diagonally with no fixed baseline which makes the script somewhat complex. Overlap is present not only in characters but in the ligatures as well. This paper proposes a method which allows successful recognition of Nastalique Script.Keywords: HMM, Image processing, Optical CharacterRecognition, Urdu OCR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21591480 A Structural Support Vector Machine Approach for Biometric Recognition
Authors: Vishal Awasthi, Atul Kumar Agnihotri
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Face is a non-intrusive strong biometrics for identification of original and dummy facial by different artificial means. Face recognition is extremely important in the contexts of computer vision, psychology, surveillance, pattern recognition, neural network, content based video processing. The availability of a widespread face database is crucial to test the performance of these face recognition algorithms. The openly available face databases include face images with a wide range of poses, illumination, gestures and face occlusions but there is no dummy face database accessible in public domain. This paper presents a face detection algorithm based on the image segmentation in terms of distance from a fixed point and template matching methods. This proposed work is having the most appropriate number of nodal points resulting in most appropriate outcomes in terms of face recognition and detection. The time taken to identify and extract distinctive facial features is improved in the range of 90 to 110 sec. with the increment of efficiency by 3%.Keywords: Face recognition, Principal Component Analysis, PCA, Linear Discriminant Analysis, LDA, Improved Support Vector Machine, iSVM, elastic bunch mapping technique.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4941479 Clustered Signatures for Modeling and Recognizing 3D Rigid Objects
Authors: H. B. Darbandi, M. R. Ito, J. Little
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This paper describes a probabilistic method for three-dimensional object recognition using a shared pool of surface signatures. This technique uses flatness, orientation, and convexity signatures that encode the surface of a free-form object into three discriminative vectors, and then creates a shared pool of data by clustering the signatures using a distance function. This method applies the Bayes-s rule for recognition process, and it is extensible to a large collection of three-dimensional objects.Keywords: Object recognition, modeling, classification, computer vision.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12781478 Assessment of Time-Lapse in Visible and Thermal Face Recognition
Authors: Sajad Farokhi, Siti Mariyam Shamsuddin, Jan Flusser, Usman Ullah Sheikh
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Although face recognition seems as an easy task for human, automatic face recognition is a much more challenging task due to variations in time, illumination and pose. In this paper, the influence of time-lapse on visible and thermal images is examined. Orthogonal moment invariants are used as a feature extractor to analyze the effect of time-lapse on thermal and visible images and the results are compared with conventional Principal Component Analysis (PCA). A new triangle square ratio criterion is employed instead of Euclidean distance to enhance the performance of nearest neighbor classifier. The results of this study indicate that the ideal feature vectors can be represented with high discrimination power due to the global characteristic of orthogonal moment invariants. Moreover, the effect of time-lapse has been decreasing and enhancing the accuracy of face recognition considerably in comparison with PCA. Furthermore, our experimental results based on moment invariant and triangle square ratio criterion show that the proposed approach achieves on average 13.6% higher in recognition rate than PCA.Keywords: Infrared Face recognition, Time-lapse, Zernike moment invariants
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17841477 Animal-Assisted Therapy for Persons with Disabilities Based on Canine Tail Language Interpretation via Gaussian-Trapezoidal Fuzzy Emotional Behavior Model
Authors: W. Phanwanich, O. Kumdee, P. Ritthipravat, Y. Wongsawat
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In order to alleviate the mental and physical problems of persons with disabilities, animal-assisted therapy (AAT) is one of the possible modalities that employs the merit of the human-animal interaction. Nevertheless, to achieve the purpose of AAT for persons with severe disabilities (e.g. spinal cord injury, stroke, and amyotrophic lateral sclerosis), real-time animal language interpretation is desirable. Since canine behaviors can be visually notable from its tail, this paper proposes the automatic real-time interpretation of canine tail language for human-canine interaction in the case of persons with severe disabilities. Canine tail language is captured via two 3-axis accelerometers. Directions and frequencies are selected as our features of interests. The novel fuzzy rules based on Gaussian-Trapezoidal model and center of gravity (COG)-based defuzzification method are proposed in order to interpret the features into four canine emotional behaviors, i.e., agitate, happy, scare and neutral as well as its blended emotional behaviors. The emotional behavior model is performed in the simulated dog and has also been evaluated in the real dog with the perfect recognition rate.Keywords: Animal-assisted therapy (AAT), Persons with disabilities, Canine tail language, Fuzzy emotional behavior model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20181476 Using Teager Energy Cepstrum and HMM distancesin Automatic Speech Recognition and Analysis of Unvoiced Speech
Authors: Panikos Heracleous
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In this study, the use of silicon NAM (Non-Audible Murmur) microphone in automatic speech recognition is presented. NAM microphones are special acoustic sensors, which are attached behind the talker-s ear and can capture not only normal (audible) speech, but also very quietly uttered speech (non-audible murmur). As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech conversion etc.) for sound-impaired people. Using a small amount of training data and adaptation approaches, 93.9% word accuracy was achieved for a 20k Japanese vocabulary dictation task. Non-audible murmur recognition in noisy environments is also investigated. In this study, further analysis of the NAM speech has been made using distance measures between hidden Markov model (HMM) pairs. It has been shown the reduced spectral space of NAM speech using a metric distance, however the location of the different phonemes of NAM are similar to the location of the phonemes of normal speech, and the NAM sounds are well discriminated. Promising results in using nonlinear features are also introduced, especially under noisy conditions.Keywords: Speech recognition, unvoiced speech, nonlinear features, HMM distance measures
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16471475 A New Face Recognition Method using PCA, LDA and Neural Network
Authors: A. Hossein Sahoolizadeh, B. Zargham Heidari, C. Hamid Dehghani
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In this paper, a new face recognition method based on PCA (principal Component Analysis), LDA (Linear Discriminant Analysis) and neural networks is proposed. This method consists of four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii) feature extraction using LDA and iv) classification using neural network. Combination of PCA and LDA is used for improving the capability of LDA when a few samples of images are available and neural classifier is used to reduce number misclassification caused by not-linearly separable classes. The proposed method was tested on Yale face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.Keywords: Face recognition Principal component analysis, Linear discriminant analysis, Neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32131474 A Weighted Approach to Unconstrained Iris Recognition
Authors: Yao-Hong Tsai
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This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.
Keywords: Authentication, iris recognition, Adaboost, local binary pattern.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19371473 Analysis of Feature Space for a 2d/3d Vision based Emotion Recognition Method
Authors: Robert Niese, Ayoub Al-Hamadi, Bernd Michaelis
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In modern human computer interaction systems (HCI), emotion recognition is becoming an imperative characteristic. The quest for effective and reliable emotion recognition in HCI has resulted in a need for better face detection, feature extraction and classification. In this paper we present results of feature space analysis after briefly explaining our fully automatic vision based emotion recognition method. We demonstrate the compactness of the feature space and show how the 2d/3d based method achieves superior features for the purpose of emotion classification. Also it is exposed that through feature normalization a widely person independent feature space is created. As a consequence, the classifier architecture has only a minor influence on the classification result. This is particularly elucidated with the help of confusion matrices. For this purpose advanced classification algorithms, such as Support Vector Machines and Artificial Neural Networks are employed, as well as the simple k- Nearest Neighbor classifier.Keywords: Facial expression analysis, Feature extraction, Image processing, Pattern Recognition, Application.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19231472 Efficient Feature Fusion for Noise Iris in Unconstrained Environment
Authors: Yao-Hong Tsai
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This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.
Keywords: Image fusion, iris recognition, local binary pattern, wavelet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22171471 Scenario Recognition in Modern Building Automation
Authors: Roland Lang, Dietmar Bruckner, Rosemarie Velik, Tobias Deutsch
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Modern building automation needs to deal with very different types of demands, depending on the use of a building and the persons acting in it. To meet the requirements of situation awareness in modern building automation, scenario recognition becomes more and more important in order to detect sequences of events and to react to them properly. We present two concepts of scenario recognition and their implementation, one based on predefined templates and the other applying an unsupervised learning algorithm using statistical methods. Implemented applications will be described and their advantages and disadvantages will be outlined.Keywords: Building automation, ubiquitous computing, scenariorecognition, surveillance system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16451470 Self-Efficacy, Anxiety, and Performance in the English Language among Middle-School Students in English Language Program in Satri Si Suriyothai School, Bangkok
Authors: Christopher C. Anyadubalu
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This study investigated students- perception of self efficacy and anxiety in acquiring English language, and consequently examined the relationship existing among the independent variables, confounding variables and students- performances in the English language. The researcher tested the research hypotheses using a sample group of 318 respondents out of the population size of 400 students. The results obtained revealed that there was a significant moderate negative relationship between English language anxiety and performance in English language, but no significant relationship between self-efficacy and English language performance, among the middle-school students. There was a significant moderate negative relationship between English language anxiety and self-efficacy. It was discovered that general self-efficacy and English language anxiety represented a significantly more powerful set of predictors than the set of confounding variables. Thus, the study concluded that English language anxiety and general self-efficacy were significant predictors of English language performance among middle-school students in Satri Si Suriyothai School.Keywords: Anxiety, English Language Anxiety, Performance inEnglish Language, Self Efficacy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 46871469 Improving Activity Recognition Classification of Repetitious Beginner Swimming Using a 2-Step Peak/Valley Segmentation Method with Smoothing and Resampling for Machine Learning
Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond
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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.
Keywords: Time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2061468 Hand Gesture Recognition using Blob Detection for Immersive Projection Display System
Authors: Hasup Lee, Yoshisuke Tateyama, Tetsuro Ogi
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We developed a vision interface immersive projection system, CAVE in virtual rea using hand gesture recognition with computer vis background image was subtracted from current webcam and we convert the color space of the imag Then we mask skin regions using skin color range t a noise reduction operation. We made blobs fro gestures were recognized using these blobs. Using recognition, we could implement an effective bothering devices for CAVE. e framework for an reality research field vision techniques. ent image frame age into HSV space. e threshold and apply from the image and ing our hand gesture e interface without
Keywords: CAVE, Computer Vision, Ges Virtual Reality esture Recognition,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27571467 Key Factors of Curriculum Innovation in Language Teacher Education
Authors: Liliana Mâţă
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The focus of the study is to understand the factors of curriculum innovation from the perspective of Language teacher education. The overall aim of the study is to investigate Language educators- perceptions of factors of curriculum innovation. In the theoretical framework the main focus is on discussion about different curriculum approaches for language teacher education and limiting and facilitating factors of innovation. In order to achieve the aim of the study, an observational research is employed. The empirical basis of the study consists of questionnaire with sixty-three language teachers from eight Romanian higher education institutions. The findings reveal variation in Language teachers- conceptions of the dominant factors of curricular innovation.Keywords: curriculum innovation, factors, Language teacher education
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 168271466 Named Entity Recognition using Support Vector Machine: A Language Independent Approach
Authors: Asif Ekbal, Sivaji Bandyopadhyay
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Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is now-a-days considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali and Hindi using Support Vector Machine (SVM). Though this state of the art machine learning technique has been widely applied to NER in several well-studied languages, the use of this technique to Indian languages (ILs) is very new. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the four different named (NE) classes, such as Person name, Location name, Organization name and Miscellaneous name. We have used the annotated corpora of 122,467 tokens of Bengali and 502,974 tokens of Hindi tagged with the twelve different NE classes 1, defined as part of the IJCNLP-08 NER Shared Task for South and South East Asian Languages (SSEAL) 2. In addition, we have manually annotated 150K wordforms of the Bengali news corpus, developed from the web-archive of a leading Bengali newspaper. We have also developed an unsupervised algorithm in order to generate the lexical context patterns from a part of the unlabeled Bengali news corpus. Lexical patterns have been used as the features of SVM in order to improve the system performance. The NER system has been tested with the gold standard test sets of 35K, and 60K tokens for Bengali, and Hindi, respectively. Evaluation results have demonstrated the recall, precision, and f-score values of 88.61%, 80.12%, and 84.15%, respectively, for Bengali and 80.23%, 74.34%, and 77.17%, respectively, for Hindi. Results show the improvement in the f-score by 5.13% with the use of context patterns. Statistical analysis, ANOVA is also performed to compare the performance of the proposed NER system with that of the existing HMM based system for both the languages.
Keywords: Named Entity (NE), Named Entity Recognition (NER), Support Vector Machine (SVM), Bengali, Hindi.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34041465 Normalization Discriminant Independent Component Analysis
Authors: Liew Yee Ping, Pang Ying Han, Lau Siong Hoe, Ooi Shih Yin, Housam Khalifa Bashier Babiker
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In face recognition, feature extraction techniques attempts to search for appropriate representation of the data. However, when the feature dimension is larger than the samples size, it brings performance degradation. Hence, we propose a method called Normalization Discriminant Independent Component Analysis (NDICA). The input data will be regularized to obtain the most reliable features from the data and processed using Independent Component Analysis (ICA). The proposed method is evaluated on three face databases, Olivetti Research Ltd (ORL), Face Recognition Technology (FERET) and Face Recognition Grand Challenge (FRGC). NDICA showed it effectiveness compared with other unsupervised and supervised techniques.
Keywords: Face recognition, small sample size, regularization, independent component analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19551464 Make Up Flash: Web Application for the Improvement of Physical Appearance in Images Based on Recognition Methods
Authors: Stefania Arguelles Reyes, Octavio José Salcedo Parra, Alberto Acosta López
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This paper presents a web application for the improvement of images through recognition. The web application is based on the analysis of picture-based recognition methods that allow an improvement on the physical appearance of people posting in social networks. The basis relies on the study of tools that can correct or improve some features of the face, with the help of a wide collection of user images taken as reference to build a facial profile. Automatic facial profiling can be achieved with a deeper study of the Object Detection Library. It was possible to improve the initial images with the help of MATLAB and its filtering functions. The user can have a direct interaction with the program and manually adjust his preferences.
Keywords: Application, MATLAB, make up, model, recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5711463 Bi-lingual Handwritten Character and Numeral Recognition using Multi-Dimensional Recurrent Neural Networks (MDRNN)
Authors: Kandarpa Kumar Sarma
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The key to the continued success of ANN depends, considerably, on the use of hybrid structures implemented on cooperative frame-works. Hybrid architectures provide the ability to the ANN to validate heterogeneous learning paradigms. This work describes the implementation of a set of Distributed and Hybrid ANN models for Character Recognition applied to Anglo-Assamese scripts. The objective is to describe the effectiveness of Hybrid ANN setups as innovative means of neural learning for an application like multilingual handwritten character and numeral recognition.Keywords: Assamese, Feature, Recurrent.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15321462 A Modified Speech Enhancement Using Adaptive Gain Equalizer with Non linear Spectral Subtraction for Robust Speech Recognition
Authors: C. Ganesh Babu, P. T. Vanathi
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In this paper we present an enhanced noise reduction method for robust speech recognition using Adaptive Gain Equalizer with Non linear Spectral Subtraction. In Adaptive Gain Equalizer method (AGE), the input signal is divided into a number of subbands that are individually weighed in time domain, in accordance to the short time Signal-to-Noise Ratio (SNR) in each subband estimation at every time instant. Instead of focusing on suppression the noise on speech enhancement is focused. When analysis was done under various noise conditions for speech recognition, it was found that Adaptive Gain Equalizer method algorithm has an obvious failing point for a SNR of -5 dB, with inadequate levels of noise suppression for SNR less than this point. This work proposes the implementation of AGE when coupled with Non linear Spectral Subtraction (AGE-NSS) for robust speech recognition. The experimental result shows that out AGE-NSS performs the AGE when SNR drops below -5db level.
Keywords: Adaptive Gain Equalizer, Non Linear Spectral Subtraction, Speech Enhancement, and Speech Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17031461 Myanmar Character Recognition Using Eight Direction Chain Code Frequency Features
Authors: Kyi Pyar Zaw, Zin Mar Kyu
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Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.
Keywords: Chain code frequency, character recognition, feature extraction, features matching, segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7531460 A Computer Model of Language Acquisition – Syllable Learning – Based on Hebbian Cell Assemblies and Reinforcement Learning
Authors: Sepideh Fazeli, Fariba Bahrami
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Investigating language acquisition is one of the most challenging problems in the area of studying language. Syllable learning as a level of language acquisition has a considerable significance since it plays an important role in language acquisition. Because of impossibility of studying language acquisition directly with children, especially in its developmental phases, computer models will be useful in examining language acquisition. In this paper a computer model of early language learning for syllable learning is proposed. It is guided by a conceptual model of syllable learning which is named Directions Into Velocities of Articulators model (DIVA). The computer model uses simple associational and reinforcement learning rules within neural network architecture which are inspired by neuroscience. Our simulation results verify the ability of the proposed computer model in producing phonemes during babbling and early speech. Also, it provides a framework for examining the neural basis of language learning and communication disorders.Keywords: Brain modeling, computer models, language acquisition, reinforcement learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15911459 A New Approach for Mobile Agent Security
Authors: R. Haghighat far, H. Yarahmadi
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A mobile agent is a software which performs an action autonomously and independently as a person or an organizations assistance. Mobile agents are used for searching information, retrieval information, filtering, intruder recognition in networks, and so on. One of the important issues of mobile agent is their security. It must consider different security issues in effective and secured usage of mobile agent. One of those issues is the integrity-s protection of mobile agents. In this paper, the advantages and disadvantages of each method, after reviewing the existing methods, is examined. Regarding to this matter that each method has its own advantage or disadvantage, it seems that by combining these methods, one can reach to a better method for protecting the integrity of mobile agents. Therefore, this method is provided in this paper and then is evaluated in terms of existing method. Finally, this method is simulated and its results are the sign of improving the possibility of integrity-s protection of mobile agents.Keywords: Integrity, Mobile Agent, Security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17591458 Video-Based Face Recognition Based On State-Space Model
Authors: Cheng-Chieh Chiang, Yi-Chia Chan, Greg C. Lee
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This paper proposes a video-based framework for face recognition to identify which faces appear in a video sequence. Our basic idea is like a tracking task - to track a selection of person candidates over time according to the observing visual features of face images in video frames. Hence, we employ the state-space model to formulate video-based face recognition by dividing this problem into two parts: the likelihood and the transition measures. The likelihood measure is to recognize whose face is currently being observed in video frames, for which two-dimensional linear discriminant analysis is employed. The transition measure estimates the probability of changing from an incorrect recognition at the previous stage to the correct person at the current stage. Moreover, extra nodes associated with head nodes are incorporated into our proposed state-space model. The experimental results are also provided to demonstrate the robustness and efficiency of our proposed approach.
Keywords: 2DLDA, face recognition, state-space model, likelihood measure, transition measure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16861457 E-Voting: A Trustworthiness In Democratic; A View from Technology, Political and Social Issue
Authors: Sera Syarmila Sameon, Rohaini Ramli
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A trustworthy voting process in democratic is important that each vote is recorded with accuracy and impartiality. The accuracy and impartiality are tallied in high rate with biometric system. One of the sign is a fingerprint. Fingerprint recognition is still a challenging problem, because of the distortions among the different impression of the same finger. Because of the trustworthy of biometric voting technologies, it may give a great effect on numbers of voter-s participation and outcomes of the democratic process. Hence in this study, the authors are interested in designing and analyzing the Electronic Voting System and the participation of the users. The system is based on the fingerprint minutiae with the addition of person ID number. This is in order to enhance the accuracy and speed of the voting process. The new design is analyzed by conducting pilot election among a class of students for selecting their representative.Keywords: Biometric, FAR and FRR, democratic, voting
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15701456 On-line Recognition of Isolated Gestures of Flight Deck Officers (FDO)
Authors: Deniz T. Sodiri, Venkat V S S Sastry
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The paper presents an on-line recognition machine (RM) for continuous/isolated, dynamic and static gestures that arise in Flight Deck Officer (FDO) training. RM is based on generic pattern recognition framework. Gestures are represented as templates using summary statistics. The proposed recognition algorithm exploits temporal and spatial characteristics of gestures via dynamic programming and Markovian process. The algorithm predicts corresponding index of incremental input data in the templates in an on-line mode. Accumulated consistency in the sequence of prediction provides a similarity measurement (Score) between input data and the templates. The algorithm provides an intuitive mechanism for automatic detection of start/end frames of continuous gestures. In the present paper, we consider isolated gestures. The performance of RM is evaluated using four datasets - artificial (W TTest), hand motion (Yang) and FDO (tracker, vision-based ). RM achieves comparable results which are in agreement with other on-line and off-line algorithms such as hidden Markov model (HMM) and dynamic time warping (DTW). The proposed algorithm has the additional advantage of providing timely feedback for training purposes.Keywords: On-line Recognition Algorithm, IsolatedDynamic/Static Gesture Recognition, On-line Markovian/DynamicProgramming, Training in Virtual Environments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13321455 A New Approach to ECG Biometric Systems: A Comparitive Study between LPC and WPD Systems
Authors: Justin Leo Cheang Loong, Khazaimatol S Subari, Rosli Besar, Muhammad Kamil Abdullah
Abstract:
In this paper, a novel method for a biometric system based on the ECG signal is proposed, using spectral coefficients computed through linear predictive coding (LPC). ECG biometric systems have traditionally incorporated characteristics of fiducial points of the ECG signal as the feature set. These systems have been shown to contain loopholes and thus a non-fiducial system allows for tighter security. In the proposed system, incorporating non-fiducial features from the LPC spectrum produced a segment and subject recognition rate of 99.52% and 100% respectively. The recognition rates outperformed the biometric system that is based on the wavelet packet decomposition (WPD) algorithm in terms of recognition rates and computation time. This allows for LPC to be used in a practical ECG biometric system that requires fast, stringent and accurate recognition.
Keywords: biometric, ecg, linear predictive coding, wavelet packet decomposition
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2903