Phonological mean length of utterance (PMLU) is a whole word measure for measuring phonological proficiency. It measures the length of a child’s word and the number of correct consonants. The present study investigated the phonological length of utterance in native Kannada speaking children of 3 to 7 years age. A total of 400 subjects in the age range of 3-7 years participated in the study. Spontaneous speech samples were elicited from each child and analyzed for PMLU as per the rules suggested by Ingram. Mann-Whitney U test and Kruskal Wallis test were employed to compare the differences between the means of PMLU scores across the gender and the age respectively. The result revealed increase in PMLU score as the age increased suggesting a developmental trend in PMLU acquisition. No statistically significant differences were observed between the means of PMLU scores across the gender.

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LANGUAGE IN INDIA Strength for Today and Bright Hope for Tomorrow

The term Machine Translation is a standard name for computerized systems responsible for the production of translations from one natural language into another with or without human assistance. It is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. Many attempts are being made all over the world to develop machine translation systems for various languages using rule-based as well as statistically based approaches. Development of a full-fledged bilingual machine translation (MT) system for any two natural languages with limited electronic resources and tools is a challenging and demanding task. In order to achieve reasonable translation quality in open source tasks, corpus based machine translation approaches require large amounts of parallel corpora that are not always available, especially for less resourced language pairs. On the other hand, the rule-based machine translation process is extremely time consuming, difficult, and fails to analyze accurately a large corpus of unrestricted text. Even though there has been effort towards building English to Indian language and Indian language to Indian language translation system, unfortunately, we do not have an efficient translation system as of today. The literature shows that there have been many attempts in MT for English to Indian languages and Indian languages to Indian languages. At present, a number of government and private sector projects are working towards developing a full-fledged MT for Indian languages. This paper gives a brief description of the various approaches and major machine translation developments in India.

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Machine Translation Approaches and Survey for Indian Languages

Problem statement: In a large multilingual society like India, there i s a great demand for translation of documents from one language to anoth er language. Approach: Most of the state government works in there provincial languages, whereas the central government's official documents and reports are in English and Hindi. Results: In order to have an appropriate communication ther e is a need to translate these documents and reports in the respective provincial languages. Natural Language Processing (NLP) and Machine Translation (MT) tools are upcoming areas of study the field of computational linguistics. Machine translation i s the application of computers to the translation o f texts from one natural language into another natura l language. It is an important sub-discipline of th e wider field of artificial intelligence. Conclusion/Recommendations: There are certain machine translation systems that have been developed in Ind ia for translation from English to Indian languages by using different approaches. It is this perspecti ve with which we shall broach this study, launching our theme with a brief on the machine translation s ystems scenario in India through data and previous research on machine translation.

Machine Translation System in Indian Perspectives

In this paper we examine the behavior of Ad Hoc networks through simulations, using different routing protocols and various topologies. We examine the difference in performance, using CBR application, with packets of different size through a variety of topologies, showing the impact node placement has on networks performance. We show that the choice of routing protocol plays an important role on network’s performance. We also quantify node mobility effects, by looking into both static and fully mobile configurations. Our paper presents a systematic analysis of a variety of different ad hoc network topologies in terms of node placement, node mobility and routing protocols through several simulated scenarios.

IJCSI Publicity Board 2010

We present a compendium of 110 Statistical Machine Translation systems built from parallel corpora of 11 Indian languages belonging to both Indo-Aryan and Dravidian families. We analyze the relationship between translation accuracy and the language families involved. We feel that insights obtained from this analysis will provide guidelines for creating machine translation systems of specific Indian language pairs. We build phrase based systems and some extensions. Across multiple languages, we show improvements on the baseline phrase based systems using these extensions: (1) source side reordering for English-Indian language translation, and (2) transliteration of untranslated words for Indian language-Indian language translation. These enhancements harness shared characteristics of Indian languages. To stimulate similar innovation widely in the NLP community, we have made the trained models for these language pairs publicly available.

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Shata-Anuvadak: Tackling Multiway Translation of Indian Languages

Interlingua and transfer-based approaches to machine translation have long been in use in competing and complementary ways. The former proves economical in situations where translation among multiple languages is involved, and can be used as a knowledge-representation scheme. But given a particular interlingua, its adoption depends on its ability (a) to capture the knowledge in texts precisely and accurately and (b) to handle cross-language divergences. This paper studies the language divergence between English and Hindi and its implication to machine translation between these languages using the Universal Networking Language (UNL). UNL has been introduced by the United Nations University, Tokyo, to facilitate the transfer and exchange of information over the internet. The representation works at the level of single sentences and defines a semantic net-like structure in which nodes are word concepts and arcs are semantic relations between these concepts. The language divergences between Hindi, an Indo-European language, and English can be considered as representing the divergences between the SOV and SVO classes of languages. The work presented here is the only one to our knowledge that describes language divergence phenomena in the framework of computational linguistics through a South Asian language.

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Jignashu Parikh

Papers

Interlingua-based English–Hindi Machine Translation and Language Divergence