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Shyam, R.
- A Fast and Efficient Framework for Creating Parallel Corpus
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Authors
Affiliations
1 Centre for Computational Engineering and Networking (CEN),Amrita School of Engineering, Amrita University, Amrita Vishwa Vidyapeetham, Amritanagar, Coimbatore – 641 112, Tamilnadu, IN
1 Centre for Computational Engineering and Networking (CEN),Amrita School of Engineering, Amrita University, Amrita Vishwa Vidyapeetham, Amritanagar, Coimbatore – 641 112, Tamilnadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 45 (2016), Pagination:Abstract
Objectives: A framework involving Scansnap SV600 scanner and Google Optical character recognition (OCR) for creating parallel corpus which is a very essential component of Statistical Machine Translation (SMT). Methods and Analysis: Training a language model for a SMT system highly depends on the availability of a parallel corpus. An efficacious approach for collecting parallel sentences is the predominant step in an MT system. However, the creation of a parallel corpus requires extensive knowledge in both languages which is a time consuming process. Due to these limitations, making the documents digital becomes very difficult and which in turn affects the quality of machine translation systems. In this paper, we propose a faster and efficient way of generating English to Indian languages parallel corpus with less human involvement. With the help of a special type of scanner called Scansnap SV600 and Google OCR and a little linguistic knowledge, we can create a parallel corpus for any language pair, provided there should be paper documents with parallel sentences. Findings: It was possible to generate 40 parallel sentences in 1 hour time with this approach. Sophisticated morphological tools were used for changing the morphology of the text generated and thereby increase the size of the corpus. An additional benefit of this is to make ancient scriptures or other manuscripts in digital format which can then be referred by the coming generation to keep up the traditions of a nation or a society. Novelty: Time required for creating parallel corpus is reduced by incorporating Google OCR and book scanner.Keywords
Google OCR, Machine Translation, Parallel Corpus, Statistical Machine Translation, Scansnap SV600 Scanner.Full Text
- Static Modelling, Automation and Control of PRR Parallel Manipulator
Abstract Views :157 |
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Authors
Ganesh Mangavu
1,
P. Kalyan Kaushik
1,
Utsav Ranjan
1,
R. Shyam
1,
N. S. Mithun
1,
Anjan Kumar Dash
1
Affiliations
1 School of Mechanical Engineering, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN
1 School of Mechanical Engineering, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 23 (2015), Pagination:Abstract
Background/Objectives: Parallel manipulators edge over serial manipulators for their performance characteristics such as high accuracy and low inertia. In this paper, PRR planar parallel manipulator with elevated links was studied and analyzed. Methods/Statistical Analysis: Kinematic simulation was carried out and the workspace of the manipulator was determined. Static analysis including stress analysis, torque and inertia computations was made. Stress analysis of manipulator was done by ANSYS. Findings: Simple analytical method was employed for finding workspace area. The load bearing capability of the non planar links was high compared to the planar links. The inertia computations of the lead screw and the inclined links provide promising results for system dynamics. Application/Improvements: Non-planar links will be useful for manipulators facing challenges in dynamics.Keywords
Moment of Inertia, Non-Planar Links, Planar Parallel Manipulator, Stiffness, Stress Analysis.Full Text