Vinodh Rajan | University of St Andrews (original) (raw)
I am currently studying for my PhD in Computer Science at the University of St Andrews in the SACHI research group. My PhD research is concerned innovative methods of performing quantitative digital paleeographic analysis. My other research interests include Machine Transliteration, Indic Language Computing and Digital Humanities.
For more information about me visit my personal site: http://www.virtualvinodh.com
Supervisors: Mark-Jan Nederhof
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Papers by Vinodh Rajan
Digital Scholarship in the Humanities, 2016
Analysis of scripts plays an important role in paleography and in quantitative linguistics. Espec... more Analysis of scripts plays an important role in paleography and in quantitative linguistics. Especially in the field of digital paleography quantitative features are much needed to differentiate glyphs. We describe an elaborate set of metrics that quantify qualitative information contained in characters and hence indirectly also quantify the scribal features. We broadly divide the metrics into several categories and describe each individual metric with its underlying qualitative significance. The metrics are largely derived from the related area of gesture design and recognition. We also propose several novel metrics. The proposed metrics are soundly grounded on the principles of handwriting production and handwriting analysis. These computed metrics could serve as descriptors for scripts and also be used for comparing and analyzing scripts. We illustrate some quantitative analysis based on the proposed metrics by applying it to the paleographic evolution of the medieval Tamil script from Brahmi. We also outline future work.
Proceedings of Digital Humanities, DH 2014, 2014
Proceedings of the 17th International Graphonomics Society Conference, 2015
Indic scripts are among few scripts in the world that have had continuous development for more t... more Indic scripts are among few scripts in the world that have had continuous development for more than two millennia. The modern forms of the scripts are the result of infinitesimal changes in handwriting being accumulated over centuries. They present us with a unique opportunity to understand various changes occurring in handwriting behavior. We have taken four major Indic scripts in six different stages of evolution and extracted features quantifying their handwriting behavior. We have derived these features by applying the principles of handwriting production and gesture analysis on a paleographic data set. We present various trends and behaviors that occurred during script development and discuss our interpretation of the results in terms of evolution of handwriting behavior. We then briefly discuss the detailed analyses that will be performed on the dataset in the future. We also consider the applications of these results in digital paleography and handwriting-driven systems.
Proceedings of the 5th Workshop on South and South-East Asian Natural Language Processing, COLING 2014, 2014
We have developed a finite state transducer based transliteration engine called Konkanverter that... more We have developed a finite state transducer based transliteration engine called Konkanverter that performs statistical machine transliteration between three different scripts used to write the Konkani language. The statistical machine transliteration system consists of cascading finite state transducers combining both rule-based and statistical approaches. Based on the limited availability of parallel corpora, this cascading approach is found to perform significantly better than a pure rule-based approach or pure statistical approach.
Digital Scholarship in the Humanities, 2016
Analysis of scripts plays an important role in paleography and in quantitative linguistics. Espec... more Analysis of scripts plays an important role in paleography and in quantitative linguistics. Especially in the field of digital paleography quantitative features are much needed to differentiate glyphs. We describe an elaborate set of metrics that quantify qualitative information contained in characters and hence indirectly also quantify the scribal features. We broadly divide the metrics into several categories and describe each individual metric with its underlying qualitative significance. The metrics are largely derived from the related area of gesture design and recognition. We also propose several novel metrics. The proposed metrics are soundly grounded on the principles of handwriting production and handwriting analysis. These computed metrics could serve as descriptors for scripts and also be used for comparing and analyzing scripts. We illustrate some quantitative analysis based on the proposed metrics by applying it to the paleographic evolution of the medieval Tamil script from Brahmi. We also outline future work.
Proceedings of Digital Humanities, DH 2014, 2014
Proceedings of the 17th International Graphonomics Society Conference, 2015
Indic scripts are among few scripts in the world that have had continuous development for more t... more Indic scripts are among few scripts in the world that have had continuous development for more than two millennia. The modern forms of the scripts are the result of infinitesimal changes in handwriting being accumulated over centuries. They present us with a unique opportunity to understand various changes occurring in handwriting behavior. We have taken four major Indic scripts in six different stages of evolution and extracted features quantifying their handwriting behavior. We have derived these features by applying the principles of handwriting production and gesture analysis on a paleographic data set. We present various trends and behaviors that occurred during script development and discuss our interpretation of the results in terms of evolution of handwriting behavior. We then briefly discuss the detailed analyses that will be performed on the dataset in the future. We also consider the applications of these results in digital paleography and handwriting-driven systems.
Proceedings of the 5th Workshop on South and South-East Asian Natural Language Processing, COLING 2014, 2014
We have developed a finite state transducer based transliteration engine called Konkanverter that... more We have developed a finite state transducer based transliteration engine called Konkanverter that performs statistical machine transliteration between three different scripts used to write the Konkani language. The statistical machine transliteration system consists of cascading finite state transducers combining both rule-based and statistical approaches. Based on the limited availability of parallel corpora, this cascading approach is found to perform significantly better than a pure rule-based approach or pure statistical approach.