15 resultados para Translation training

em Cochin University of Science


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This paper underlines a methodology for translating text from English into the Dravidian language, Malayalam using statistical models. By using a monolingual Malayalam corpus and a bilingual English/Malayalam corpus in the training phase, the machine automatically generates Malayalam translations of English sentences. This paper also discusses a technique to improve the alignment model by incorporating the parts of speech information into the bilingual corpus. Removing the insignificant alignments from the sentence pairs by this approach has ensured better training results. Pre-processing techniques like suffix separation from the Malayalam corpus and stop word elimination from the bilingual corpus also proved to be effective in training. Various handcrafted rules designed for the suffix separation process which can be used as a guideline in implementing suffix separation in Malayalam language are also presented in this paper. The structural difference between the English Malayalam pair is resolved in the decoder by applying the order conversion rules. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics

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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

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In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam translation using statistical models like translation model, language model and a decoder. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set up among the sentence pairs of the source and target language before subjecting them for training. This paper is deals with the techniques which can be adopted for improving the alignment model of SMT. Incorporating the parts of speech information into the bilingual corpus has eliminated many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics

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Indian marine engineers are renowned for employment globally due to their knowledge, skill and reliability. This praiseworthy status has been achieved mainly due to the systematic training imparted to marine engineering cadets. However, in an era of advancing technology, marine engineering training has to remain dynamic to imbibe latest technology as well as to meet the demands of the shipping industry. New subjects of studies have to be included in the curriculum in a timely manner taking into consideration the industry requirements and best practices in shipping. Technical competence of marine engineers also has to be subjected to changes depending upon the needs of the ever growing and over regulated shipping industry. Besides. certain soft skills are to be developed and improved amongst the marine engineers in order to alter or amend the personality traits leading to their career success.If timely corrective action is taken. Indian marine engineers can be in still greater demand for employment in global maritime field. In order to enhance the employability of our mmine engineers by improving their quality, a study of marine engineers in general and class IV marine engineers in particular was conducted based on three distinct surveys, viz., survey among senior marine engineers, survey among employers of marine engineers and survey of class IV marine engineers themselves.The surveys have been planned and questionnaires have been designed to focus the study of marine engineer officer class IV from the point of view of the three distinct groups of maritime personnels. As a result of this, the strength and weakness of class IV marine engineers are identified with regard to their performance on board ships, acquisition of necessary technical skills. employability and career success. The criteria of essential qualities of a marine engineer are classified as academic, technical, social, psychological. physical, mental, emergency responsive, communicative and leadership, and have been assessed for a practicing marine engineer by statistical analysis of data collected from surveys. These are assessed for class IV marine engineers from the point of view of senior marine engineers and employers separately. The Endings are delineated and graphically depicted in this thesis.Besides. six pertinent personality traits of a marine engineer viz. self esteem. learning style. decision making. motivation. team work and listening self inventory have been subjected to study and their correlation with career success have been established wherever possible. This is carried out to develop a theoretical framework to understand what leads a marine engineer to his career attainment. This enables the author to estimate the personality strengths and weaknesses of a serving marine engineer and eventually to deduce possible corrective measures or modifications in marine engineering training in India.Maritime training is largely based on International Conventions on Standard of Training. Certification and Watch keeping for Seafarers 1995. its associated Code and Merchant Shipping (STCW for Seafarers) Rules 1998. Further, Maritime Education, Training and Assessment (META) Manual was subjected to a critical scrutiny and relevant Endings of thc surveys arc superimposed on the existing rule requirement and curriculum. Views of senior marine engineers and executives of various shipping companies are taken into account before arriving at the revision of syllabus of marine engineering courses. Modifications in the pattern of workshop and sea service for graduate mechanical engineering trainees are recommended. Desirable age brackets of junior engineers and chief engineers. use of Training and Assessment Record book (TAR Book) during training etc. have also been evaluated.As a result of the pedagogic introspection of the existing system of marine engineering training in India. in this thesis, a revised pattern of workshop training of six months duration for graduate mechanical engineers. revised pattern of sea service training of one year duration and modified now diagram incorporating the above have been arrived at. Effects of various personality traits on career success have been established along with certain findings for improvement of desirable personality traits of marine engineers.

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This study analyses the socio-economic backgrounds and entrepreneurial profiles of the students and pass outs of the Vocational Higher Secondary Education in Kerala and the academic achievements of the Vocational Higher Secondary students and pass outs in Kerala in terms of their performance in the examinations. The study also analyses the quality and availability of the various training and support facilities of the Vocational Higher Secondary Schools in Kerala, nature and rate of employment and higher studies among the pass outs of the Vocational Higher Secondary Education in Kerala and the awareness of students, pass outs, teachers and principals regarding the goals and objectives, mode of implementation, apprenticeship training and higher study and employment opportunities of the programme of the Vocational Higher Secondary Education in Kerala.

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Public undertakings have been assigned a significant role to play in the systematic socio-economic development of India. My interest in the subject was kindled while I was doing my Masters Diploma in Public Administration at the Indian Institute of Public Administration, New Delhi during 1960-61. It was further strengthened by my teaching of the subject in different courses offered by me at the School of Management Studies and in several programmes organised by various voluntary and training organisations like the Institute of Management in Government, Trivandrum, Centre for Management Development, Trivandrum, etc. The several years in which I served as a member of the faculty in the School of Management Studies, University of Cochin,gave me the opportunity to come into close contact with different public sector concerns and their managers at various levels. This rich opportunity gave me a better insight into the problems faced by these concerns. The present study is a result of the interest so developed.

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This thesis summarizes the results on the studies on a syntax based approach for translation between Malayalam, one of Dravidian languages and English and also on the development of the major modules in building a prototype machine translation system from Malayalam to English. The development of the system is a pioneering effort in Malayalam language unattempted by previous researchers. The computational models chosen for the system is first of its kind for Malayalam language. An in depth study has been carried out in the design of the computational models and data structures needed for different modules: morphological analyzer , a parser, a syntactic structure transfer module and target language sentence generator required for the prototype system. The generation of list of part of speech tags, chunk tags and the hierarchical dependencies among the chunks required for the translation process also has been done. In the development process, the major goals are: (a) accuracy of translation (b) speed and (c) space. Accuracy-wise, smart tools for handling transfer grammar and translation standards including equivalent words, expressions, phrases and styles in the target language are to be developed. The grammar should be optimized with a view to obtaining a single correct parse and hence a single translated output. Speed-wise, innovative use of corpus analysis, efficient parsing algorithm, design of efficient Data Structure and run-time frequency-based rearrangement of the grammar which substantially reduces the parsing and generation time are required. The space requirement also has to be minimised

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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.

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In this paper we describe the methodology and the structural design of a system that translates English into Malayalam using statistical models. A monolingual Malayalam corpus and a bilingual English/Malayalam corpus are the main resource in building this Statistical Machine Translator. Training strategy adopted has been enhanced by PoS tagging which helps to get rid of the insignificant alignments. Moreover, incorporating units like suffix separator and the stop word eliminator has proven to be effective in bringing about better training results. In the decoder, order conversion rules are applied to reduce the structural difference between the language pair. The quality of statistical outcome of the decoder is further improved by applying mending rules. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics

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A methodology for translating text from English into the Dravidian language, Malayalam using statistical models is discussed in this paper. The translator utilizes a monolingual Malayalam corpus and a bilingual English/Malayalam corpus in the training phase and generates automatically the Malayalam translation of an unseen English sentence. Various techniques to improve the alignment model by incorporating the morphological inputs into the bilingual corpus are discussed. Removing the insignificant alignments from the sentence pairs by this approach has ensured better training results. Pre-processing techniques like suffix separation from the Malayalam corpus and stop word elimination from the bilingual corpus also proved to be effective in producing better alignments. Difficulties in translation process that arise due to the structural difference between the English Malayalam pair is resolved in the decoding phase by applying the order conversion rules. The handcrafted rules designed for the suffix separation process which can be used as a guideline in implementing suffix separation in Malayalam language are also presented in this paper. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics

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Statistical Machine Translation (SMT) is one of the potential applications in the field of Natural Language Processing. The translation process in SMT is carried out by acquiring translation rules automatically from the parallel corpora. However, for many language pairs (e.g. Malayalam- English), they are available only in very limited quantities. Therefore, for these language pairs a huge portion of phrases encountered at run-time will be unknown. This paper focuses on methods for handling such out-of-vocabulary (OOV) words in Malayalam that cannot be translated to English using conventional phrase-based statistical machine translation systems. The OOV words in the source sentence are pre-processed to obtain the root word and its suffix. Different inflected forms of the OOV root are generated and a match is looked up for the word variants in the phrase translation table of the translation model. A Vocabulary filter is used to choose the best among the translations of these word variants by finding the unigram count. A match for the OOV suffix is also looked up in the phrase entries and the target translations are filtered out. Structuring of the filtered phrases is done and SMT translation model is extended by adding OOV with its new phrase translations. By the results of the manual evaluation done it is observed that amount of OOV words in the input has been reduced considerably

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In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam sentence using statistical models. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set among the sentence pairs of the source and target language before subjecting them for training. This paper deals with certain techniques which can be adopted for improving the alignment model of SMT. Methods to incorporate the parts of speech information into the bilingual corpus has resulted in eliminating many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Presence of Malayalam words with predictable translations has also contributed in reducing the insignificant alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics.

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Suffix separation plays a vital role in improving the quality of training in the Statistical Machine Translation from English into Malayalam. The morphological richness and the agglutinative nature of Malayalam make it necessary to retrieve the root word from its inflected form in the training process. The suffix separation process accomplishes this task by scrutinizing the Malayalam words and by applying sandhi rules. In this paper, various handcrafted rules designed for the suffix separation process in the English Malayalam SMT are presented. A classification of these rules is done based on the Malayalam syllable preceding the suffix in the inflected form of the word (check_letter). The suffixes beginning with the vowel sounds like ആല, ഉെെ, ഇല etc are mainly considered in this process. By examining the check_letter in a word, the suffix separation rules can be directly applied to extract the root words. The quick look up table provided in this paper can be used as a guideline in implementing suffix separation in Malayalam language