Interlingua-based English–Hindi Machine Translation and Language Divergence

Interlingua and transfer-based approaches tomachine 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.     

Microblog summarization using self-adaptive multi-objective binary differential evolution

Social media platforms become paramount for gathering relevant information during the occurrence of any natural disaster. Twitter has emerged as a platform which is heavily used for the purpose of communication during disaster events. Therefore, it becomes necessary to design a technique which can summarize the relevant tweets and thus, can help in the decision-making process of disaster management authority. In this paper, the problem of summarizing the relevant tweets is posed as an optimization problem where a subset of tweets is selected using the search capability of multi-objective binary differential evolution (MOBDE) by optimizing different perspectives of the summary. MOBDE deals with a set of solutions in its population, and each solution encodes a subset of tweets. Three versions of the proposed approach, namely, MOOTS1, MOOTS2, and MOOTS3, are developed in this paper. They differ in the way of working and the adaptive selection of parameters. Recently developed self-organizing map based genetic operator is explored in the optimization process. Two measures capturing the similarity/dissimilarity between tweets, word mover distance and BM25 are explored in the optimization process. The proposed approaches are evaluated on four datasets related to disaster events containing only relevant tweets. It has been observed that all versions of the developed MOBDE framework outperform the state-of-the-art (SOA) techniques. In terms of improvements, our best-proposed approach (MOOST3) improves by 8.5% and 3.1% in terms of ROUGE??2 and ROUGE?L, respectively, over the existing techniques and these improvements are further validated using statistical significance t-test.

     

Route Visualization Using Detail Lenses

We present a method designed to address some limitations of typical route map displays of driving directions. The main goal of our system is to generate a printable version of a route map that shows the overview and detail views of the route within a single, consistent visual frame. Our proposed visualization provides a more intuitive spatial context than a simple list of turns. We present a novel multifocus technique to achieve this goal, where the foci are defined by points of interest (POI) along the route. A detail lens that encapsulates the POI at a finer geospatial scale is created for each focus. The lenses are laid out on the map to avoid occlusion with the route and each other, and to optimally utilize the free space around the route. We define a set of layout metrics to evaluate the quality of a lens layout for a given route map visualization. We compare standard lens layout methods to our proposed method and demonstrate the effectiveness of our method in generating aesthetically pleasing layouts. Finally, we perform a user study to evaluate the effectiveness of our layout choices.     

Scientific document summarization in multi-objective clustering framework

Applied Intelligence - The exponential growth in the number of scientific articles has made it difficult for the researchers to keep themselves updated with the new developments. Scientific...     

Augmenting training data with syntactic phrasal-segments in low-resource neural machine translation

Machine Translation - Neural machine translation (NMT) has emerged as a preferred alternative to the previous mainstream statistical machine translation (SMT) approaches largely due to its ability...     

Complex predicates in Indian languages and wordnets

Wordnets, which are repositories of lexical semantic knowledge containing semantically linked synsets and lexically linked words, are indispensable for work on computational linguistics and natural language processing. While building wordnets for Hindi and Marathi, two major Indo-European languages, we observed that the verb hierarchy in the Princeton Wordnet was rather shallow. We set to constructing a verb knowledge base for Hindi, which arranges the Hindi verbs in a hierarchy of is-a (hypernymy) relation. We realized that there are unique Indian language phenomena that bear upon the lexicalization vs. syntactically derived choice. One such example is the occurrence of conjunct and compound verbs (called Complex Predicates) which are found in all Indian languages. This paper presents our experience in the construction of lexical knowledge bases for Indian languages with special attention to Hindi. The question of storing versus deriving complex predicates has been dealt with linguistically and computationally. We have constructed empirical tests to decide if a combination of two words, the second of which is a verb, is a complex predicate or not. Such tests provide a principled way of deciding the status of complex predicates in Indian language wordnets.