Alignment Model and Training Technique in SMT from English to Malayalam

This paper investigates certain methods of training adopted in the Statistical Machine Translator (SMT) from English to Malayalam. In English Malayalam SMT, the word to word translation is determined by training the parallel corpus. Our primary goal is to improve the alignment model by reducing the number of possible alignments of all sentence pairs present in the bilingual corpus. Incorporating morphological information into the parallel corpus with the help of the parts of speech tagger has brought around better training results with improved accuracy

English-Malayalam Cross-Lingual Information Retrieval – an Experience

This paper describes about an English-Malayalam Cross-Lingual Information Retrieval system. The system retrieves Malayalam documents in response to query given in English or Malayalam. Thus monolingual information retrieval is also supported in this system. Malayalam is one of the most prominent regional languages of Indian subcontinent. It is spoken by more than 37 million people and is the native language of Kerala state in India. Since we neither had any full-fledged online bilingual dictionary nor any parallel corpora to build the statistical lexicon, we used a bilingual dictionary developed in house for translation. Other language specific resources like Malayalam stemmer, Malayalam morphological root analyzer etc developed in house were used in this work

Syntactic Based Machine Translation from English to Malayalam

Due to the emergence of multiple language support on the Internet, machine translation (MT) technologies are indispensable to the communication between speakers using different languages. Recent research works have started to explore tree-based machine translation systems with syntactical and morphological information. This work aims the development of Syntactic Based Machine Translation from English to Malayalam by adding different case information during translation. The system identifies general rules for various sentence patterns in English. These rules are generated using the Parts Of Speech (POS) tag information of the texts. Word Reordering based on the Syntax Tree is used to improve the translation quality of the system. The system used Bilingual English –Malayalam dictionary for translation.

Speech Analysis using Modern Techniques of Nonlinear Dynamics

Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

" Nonlinear Signal Processing of Electroencephalogram .' Application in the Study of Neurodynamics. "

Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.

Jitter measurements for Performance enhancement in the Service Sector

In a leading service economy like India, services lie at the very center of economic activity. Competitive organizations now look not only at the skills and knowledge, but also at the behavior required by an employee to be successful on the job. Emotionally competent employees can effectively deal with occupational stress and maintain psychological well-being. This study explores the scope of the first two formants and jitter to assess seven common emotional states present in the natural speech in English. The k-means method was used to classify emotional speech as neutral, happy, surprised, angry, disgusted and sad. The accuracy of classification obtained using raw jitter was more than 65 percent for happy and sad but less accurate for the others. The overall classification accuracy was 72% in the case of preprocessed jitter. The experimental study was done on 1664 English utterances of 6 females. This is a simple, interesting and more proactive method for employees from varied backgrounds to become aware of their own communication styles as well as that of their colleagues' and customers and is therefore socially beneficial. It is a cheap method also as it requires only a computer. Since knowledge of sophisticated software or signal processing is not necessary, it is easy to analyze

Service provider switching: a study on the switching process in retail banking

In a business environment that is characterized by intense competition, building customer loyalty has become a key area of focus for most financial institutions. The explosion of the services sector, changing customer demographics and deregulation and emergence of new technology in the financial services industry have had a critical impact on consumers’ financial services buying behaviour. The changes have forced banks to modify their service offerings to customers so as to ensure high levels of customer satisfaction and also high levels of customer retention. Banks have historically had difficulty distinguishing their products from one another because of their relative homogeneity; with increasing competition,the problem has only intensified with no coherent distinguishing theme. Rising wealth, product proliferation, regulatory changes and newer technologies are together making bank switching easier for customers. In order to remain competitive, it is important for banks to retain their customer base. The financial services sector is the foundation for any economy and plays the role of mobilization of resources and their allocation. The retail banking sector in India has emerged as one of the major drivers of the overall banking industry and has witnessed enormous growth. Switching behaviour has a negative impact on the banks’ market share and profitability as the costs of acquiring customers are much higher than the costs of retaining. When customers switch, the business loses the potential for additional profits from the customer the initial costs invested in the customer by the business get . The Objective of the thesis was to examine the relationship among triggers that customers experience, their perceptions of service quality, consumers’ commitment and behavioral intentions in the contemporary India retail banking context through the eyes of the customer. To understand customers’ perception of these aspects, data were collected from retail banking customers alone for the purpose of analysis, though the banks’ views were considered during the qualitative work carried out prior to the main study. No respondent who is an employee of a banking organization was considered for the final study to avoid the possibility of any bias that could affect the results adversely. The data for the study were collected from customers who have switched banks and from those who were non switchers. The study attempted to develop and validate a multidimensional construct of service quality for retail banking from the consumer’s perspective. A major conclusion from the empirical research was the confirmation of the multidimensional construct for perceived service quality in the banking context. Switching can be viewed as an optimization problem for customers; customers review the potential gains of switching to another service provider against the costs of leaving the service provider. As banks do not provide tangible products, their service quality is usually assessed through service provider’s relationship with customers. Thus, banks should pay attention towards their employees’ skills and knowledge; assessing customers’ needs and offering fast and efficient services.