Proceeding - IEEE International Conference on Computing, Communication and Automation, ICCCA 2016 | Year: 2016
Visual Speech processing is the key concern of researchers working in the field of speech processing and computer vision. Though earlier audio speech processing was popularly used for speech recognition but their performance deteriorated in the presence of noise. Moreover, variation in accent is another challenge that affects the performance of such systems. In the presented paper, we explore variation of lip texture features for recognition of visemes. The variations in temporal behavior of lip texture features is coded using Local Binary Pattern features in three orthogonal planes. The classification is carried out using the back propagation neural network, which is a network with hidden layer. The added advantage of hidden layer for lip reading is that it takes into account the nonlinear variation of lip features while speaking. The proposed approach is used for Hindi word recognition and achieved high accuracy at the cost of computation time. © 2016 IEEE.
Rathee N.,MSIT |
Vaish A.,MSIT |
Gupta S.,Indian Institute of Technology Delhi
Proceeding - IEEE International Conference on Computing, Communication and Automation, ICCCA 2016 | Year: 2016
Facial expression is the most natural way for the humans to convey their emotions with intensions. Facial expressions can be easily detected by human but for machines, it is very challenging task. In this paper, an approach for real time emotion detection is presented using real time graphic user interface for detection of emotion through a web camera. The proposed system named as Adaptive System For Recognizing State Of Mind (ASFRSOM) system is designed using the three major components: face detection, feature extraction and classification. For facial feature extraction, local binary pattern is used and the extracted features are applied to support vector machine for emotion recognition. The approach proposed in the presented work is evaluated on extended Cohn Kanade database and results in 79% accuracy. To further prove the accuracy of the proposed approach, it is used on 15 subjects in real time and emotions were accurately detected. © 2016 IEEE.
Yaduvanshi R.S.,AIT Inc |
Parthasarathy H.,Government of Delhi |
De A.,AIT Inc |
Proceedings - International Conference on Communication Systems and Network Technologies, CSNT 2012 | Year: 2012
A rotating fluid frame Antenna consisting of conducting fluid (saline water) is radiating under controlled electric field and magnetic field conditions. Water molecules oscillate due to impact ionization inside the fluid and contribute to radiate energy. Resonant frequency depends on volume, type of fluid, shape of tube, chemical properties of fluid used, DC magnetic bias and electric bias conditions. The prototype model is presented with analytical and experimental solutions. Mathematical formulations have been set up in support of detailed study of MHD antenna. The radiation patterns and impedance in this class of antenna become function of conducting fluid velocity v, magnetic field intensity H and electric fields intensity E due to Centrifugal and Coriolis forces in MHD phenomenon. Here Poynting vector of the antenna is different from the conventional type because of additional velocity field is involved. © 2012 IEEE.
Suri B.,Indraprastha University |
Jatana N.,MSIT |
Proceedings of the 2015 IEEE 3rd International Conference on MOOCs, Innovation and Technology in Education, MITE 2015 | Year: 2015
Learning Software Engineering principles, processes, methods and tools is a prerequisite to becoming a Software Engineer. The technological advancements and revolution in this new century are probing the boundaries of education and training in software engineering. This work tries to locate the shortcomings in existing approaches to Education in Software Engineering (ESE) in respect to today's technological advancements. We hereby proposed a new model for Education in Software Engineering to bridge the industry-academia gap. © 2015 IEEE.
Tushir M.,MSIT |
Applied Soft Computing Journal | Year: 2010
A possibilistic approach was initially proposed for c-means clustering. Although the possibilistic approach is sound, this algorithm tends to find identical clusters. To overcome this shortcoming, a possibilistic Fuzzy c-means algorithm (PFCM) was proposed which produced memberships and possibilities simultaneously, along with the cluster centers. PFCM addresses the noise sensitivity defect of Fuzzy c-means (FCM) and overcomes the coincident cluster problem of possibilistic c-means (PCM). Here we propose a new model called Kernel-based hybrid c-means clustering (KPFCM) where PFCM is extended by adopting a Kernel induced metric in the data space to replace the original Euclidean norm metric. Use of Kernel function makes it possible to cluster data that is linearly non-separable in the original space into homogeneous groups in the transformed high dimensional space. From our experiments, we found that different Kernels with different Kernel widths lead to different clustering results. Thus a key point is to choose an appropriate Kernel width. We have also proposed a simple approach to determine the appropriate values for the Kernel width. The performance of the proposed method has been extensively compared with a few state of the art clustering techniques over a test suit of several artificial and real life data sets. Based on computer simulations, we have shown that our model gives better results than the previous models. © 2009 Elsevier B.V. All rights reserved.
Sheoran K.,MSIT |
Tomar P.,Engineering School of Information Technology and Communication |
Mishra R.,Engineering School of Information Technology and Communication
Procedia Computer Science | Year: 2016
Software quality is regarded as the highly important factors for assessing the global competitive position of any software product. To assure quality, and to assess the reliability of software products, many software quality prediction models have been proposed in the past decades. In this proposed method we have utilized a hybrid method for quality prediction. The prediction is done with the help of the Advanced Neural network which is incorporated with Hybrid Cuckoo search (HCS) optimization algorithm for better prediction accuracy. The application software is first subjected to test case generation and once the test cases are generated they are applied to advanced neural network for the prediction of quality. The neural network is improved by utilizing HCS which optimizes the weight factor for improving the prediction. The quality metrics like maintainability and reliability are estimated for predicting the software quality and the results are compared with other existing techniques to verify the effectiveness of our proposed method. © 2016 The Authors. Published by Elsevier B.V.
Kherwa P.,MSIT |
Sachdeva A.,MSIT |
Mahajan D.,MSIT |
Pande N.,MSIT |
Souvenir of the 2014 IEEE International Advance Computing Conference, IACC 2014 | Year: 2014
The world wide web can be viewed as a repository of opinions from users spread across various websites and networks, and today's netizens look up reviews and opinions to judge commodities, visit forums to debate about events and policies. With this explosion in the volume of and reliance on user reviews and opinions, manufacturers and retailers face the challenge of automating the analysis of such big amounts of data (user reviews, opinions, sentiments). Armed with these results, sellers can enhance their product and tailor experience for the customer. Similarly, policy makers can analyse these posts to get instant and comprehensive feedback. Or use it for new ideas that democratize the policy making process. This paper is the outcome of our research in gathering opinion and review data from popular portals, e-commerce websites, forums or social networks; and processing the data using the rules of natural language and grammar to find out what exactly was being talked about in the user's review and the sentiments that people are expressing. Our approach diligently scans every line of data, and generates a cogent summary of every review (categorized by aspects) along with various graphical visualizations. A novel application of this approach is helping out product manufacturers or the government in gauging response. We aim to provide summarized positive and negative features about products, laws or policies by mining reviews, discussions, forums etc. © 2014 IEEE.
Chaturvedi K.K.,University of Delhi |
Sing V.B.,University of Delhi |
Proceedings of the 2013 13th International Conference on Computational Science and Its Applications, ICCSA 2013 | Year: 2013
Mining software repositories (MSR) is an important area of research. An international workshop on MSR has been established under the umbrella of international conference on software engineering (ICSE) in year 2004. The quality papers received and presented in the workshop has led to initiate full-fledged conference which purely focuses on issues related to mining software engineering data since 2007. This paper is the result of reviewing all the papers published in the proceedings of the conferences on Mining Software Repositories (MSR) and in other related conference/journals. We have analyzed the papers that contained experimental analysis of software projects related to data mining in software engineering. We have identified the data sets, techniques and tools used/ developed/ proposed in these papers. More than half of the papers are involved in the task accomplished by building or using the data mining tools to mine the software engineering data. It is apparent from the results obtained by analyzing these papers that MSR authors process the raw data which in general publicly available. We categorizes different tools used in MSR on the basis of newly developed, traditional data mining tools, prototype developed and scripts. We have shown the type of mining task that has been performed by using these tools along with the datasets used in these studies. © 2013 IEEE.
2016 International Conference on Computational Techniques in Information and Communication Technologies, ICCTICT 2016 - Proceedings | Year: 2016
Lip reading, also known as visual speech processing, means recognition of spoken word based on the pattern of lip movements while speaking. Audio speech recognition systems are popular since last many decades and have achieved a great success, but recently visual speech recognition has incited the interest of researchers towards lip reading. Lip reading has an added advantage of high accuracy and noise independency. This paper presents an algorithm for automatic lip reading. The algorithm consists of two main steps: feature extraction and classification for word recognition. The lip information is extracted using lip geometric and lip appearance features. The recognition of words is done by Learning Vector Quantization neural network. The accuracy achieved by proposed approach is 97%. The proposed algorithm is applied for recognition of ten words of Hindi language and can be easily extended to include more words of other languages. The presented approach will be helpful for hearing impaired or dumb people to communicate with humans or machines. The proposed algorithm is fast as well as robust to various occlusions. © 2016 IEEE.
Gahlawat M.,Deenbandhu Chhotu Ram University of Science and Technology |
Malik A.,Deenbandhu Chhotu Ram University of Science and Technology |
Biologically Inspired Cognitive Architectures | Year: 2016
Synthesis of natural sounding speech is state of the art in the field of speech technology. Imitation of the dynamic human voice is required to generate this. The aim of this work is to develop and deploy a natural speech synthesizer for visually impaired persons. The synthesizer has been developed via an integrated approach of adding localization in expressive speech using a personalized speech corpus. A genetic algorithm has been implemented for optimal selection of acoustic phonetic units of speech. This concept has many applications. We tested one of those applications here in different aspects. Its performance is compared on various categories of listeners using a subjective listening test. Encouraging results on various parameters are received from visually impaired listeners. © 2015 Elsevier B.V. All rights reserved.