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This study aims to conduct an extensive detailed analysis of the Odia Braille reading comprehension among students with visual disability. Specifically, the study explores their reading speed and hand or finger movements. The study also aims to investigate any comprehension difficulties and reading errors they may encounter. Six students from the 9th and 10th grades, aged between 14 and 16, participated in the study. We observed participants hand movements to understand how reading errors were connected to hand movement and identify the students reading difficulties. We also evaluated the participants Odia Braille reading skills, including their reading speed (in words per minute), errors, and comprehension. The average speed of Odia Braille reader is 17.64wpm. According to the study, there was a noticeable correlation between reading speed and reading errors. As reading speed decreased, the number of reading errors tended to increase. Moreover, the study established a link between reduced Braille reading errors and improved reading comprehension. In contrast, the study found that better comprehension was associated with increased reading speed. The researchers concluded with some interesting findings about preferred Braille reading patterns. These findings have important theoretical, developmental, and methodological implications for instruction., Comment: 4 Pages, Paper accepted in Diversity and Inclusion track at CODS-COMAD 2024

A number of questionnaire based psychometric testing frameworks are globally for example OCEAN (Five factor) indicator, MBTI (Myers Brigg Type Indicator) etc. However, questionnaire based psychometric tests have some known shortcomings. This work explores whether these shortcomings can be mitigated through computer-based gaming platforms for evaluating psychometric parameters. A computer based psychometric game framework called Antarjami has been developed for evaluating OCEAN (Five factor) indicators. It investigates the feasibility of extracting psychometric parameters through computer-based games, utilizing underlying improvements in the area of modern artificial intelligence. The candidates for the test are subjected to a number scenarios as part of the computer based game and their reactions/responses are used to evaluate their psychometric parameters. As part of the study, the parameters obtained from the game were compared with those evaluated using paper based tests and scores given by a panel of psychologists. The achieved results were very promising., Comment: Submitted to CogSci 2020

n this paper, we attempt to explain the emergence of the linguistic diversity that exists across the consonant inventories of some of the major language families of the world through a complex network based growth model. There is only a single parameter for this model that is meant to introduce a small amount of randomness in the otherwise preferential attachment based growth process. The experiments with this model parameter indicates that the choice of consonants among the languages within a family are far more preferential than it is across the families. The implications of this result are twofold -- (a) there is an innate preference of the speakers towards acquiring certain linguistic structures over others and (b) shared ancestry propels the stronger preferential connection between the languages within a family than across them. Furthermore, our observations indicate that this parameter might bear a correlation with the period of existence of the language families under investigation., Comment: In EACL 2009 Workshop on Cognitive Aspects of Computational Language Acquisition

We study the self-organization of the consonant inventories through a complex network approach. We observe that the distribution of occurrence as well as cooccurrence of the consonants across languages follow a power-law behavior. The co-occurrence network of consonants exhibits a high clustering coefficient. We propose four novel synthesis models for these networks (each of which is a refinement of the earlier) so as to successively match with higher accuracy (a) the above mentioned topological properties as well as (b) the linguistic property of feature economy exhibited by the consonant inventories. We conclude by arguing that a possible interpretation of this mechanism of network growth is the process of child language acquisition. Such models essentially increase our understanding of the structure of languages that is influenced by their evolutionary dynamics and this, in turn, can be extremely useful for building future NLP applications., Comment: 8pages, 3 figures, In the proceedings of COLING 2008

The difficulties involved in spelling error detection and correction in a language have been investigated in this work through the conceptualization of SpellNet - the weighted network of words, where edges indicate orthographic proximity between two words. We construct SpellNets for three languages - Bengali, English and Hindi. Through appropriate mathematical analysis and/or intuitive justification, we interpret the different topological metrics of SpellNet from the perspective of the issues related to spell-checking. We make many interesting observations, the most significant among them being that the probability of making a real word error in a language is propotionate to the average weighted degree of SpellNet, which is found to be highest for Hindi, followed by Bengali and English., Comment: 8 pages, 3 figures, to be published in the proceedings of HLT-NAACL Workshop - TextGraphs 2

In this work, we attempt to capture patterns of co-occurrence across vowel systems and at the same time figure out the nature of the force leading to the emergence of such patterns. For this purpose we define a weighted network where the vowels are the nodes and an edge between two nodes (read vowels) signify their co-occurrence likelihood over the vowel inventories. Through this network we identify communities of vowels, which essentially reflect their patterns of co-occurrence across languages. We observe that in the assortative vowel communities the constituent nodes (read vowels) are largely uncorrelated in terms of their features and show that they are formed based on the principle of maximal perceptual contrast. However, in the rest of the communities, strong correlations are reflected among the constituent vowels with respect to their features indicating that it is the principle of feature economy that binds them together. We validate the above observations by proposing a quantitative measure of perceptual contrast as well as feature economy and subsequently comparing the results obtained due to these quantifications with those where we assume that the vowel inventories had evolved just by chance., Comment: Submitted to Advances in Complex Systems

The sound inventories of the world's languages self-organize themselves giving rise to similar cross-linguistic patterns. In this work we attempt to capture this phenomenon of self-organization, which shapes the structure of the consonant inventories, through a complex network approach. For this purpose we define the occurrence and co-occurrence networks of consonants and systematically study some of their important topological properties. A crucial observation is that the occurrence as well as the co-occurrence of consonants across languages follow a power law distribution. This property is arguably a consequence of the principle of preferential attachment. In order to support this argument we propose a synthesis model which reproduces the degree distribution for the networks to a close approximation. We further observe that the co-occurrence network of consonants show a high degree of clustering and subsequently refine our synthesis model in order to incorporate this property. Finally, we discuss how preferential attachment manifests itself through the evolutionary nature of language., Comment: 18 pages, 15 figures

Cross-linguistic similarities are reflected by the speech sound systems of languages all over the world. In this work we try to model such similarities observed in the consonant inventories, through a complex bipartite network. We present a systematic study of some of the appealing features of these inventories with the help of the bipartite network. An important observation is that the occurrence of consonants follows a two regime power law distribution. We find that the consonant inventory size distribution together with the principle of preferential attachment are the main reasons behind the emergence of such a two regime behavior. In order to further support our explanation we present a synthesis model for this network based on the general theory of preferential attachment., Comment: 8 pages, 8 figures, To be published in COLING-ACL(2006)

Speech sounds of the languages all over the world show remarkable patterns of cooccurrence. In this work, we attempt to automatically capture the patterns of cooccurrence of the consonants across languages and at the same time figure out the nature of the force leading to the emergence of such patterns. For this purpose we define a weighted network where the consonants are the nodes and an edge between two nodes (read consonants) signify their co-occurrence likelihood over the consonant inventories. Through this network we identify communities of consonants that essentially reflect their patterns of co-occurrence across languages. We test the goodness of the communities and observe that the constituent consonants frequently occur in such groups in real languages also. Interestingly, the consonants forming these communities reflect strong correlations in terms of their features, which indicate that the principle of feature economy acts as a driving force towards community formation. In order to measure the strength of this force we propose an information theoretic definition of feature economy and show that indeed the feature economy exhibited by the consonant communities are substantially better than those if the consonant inventories had evolved just by chance., Comment: 15 pages, 9 figures, To be published in Int. Jour. of Modern Phy. C