A Novel Framework for Sign Language to Text Conversion using Convolutional Neural Network

Sign language is the only way of method to communication for hearing impaired and deaf-dumb peoples. The system will recognize the signs between signers and non-signers, this will give the meaning of sign. The proposed method is helpful for the people who have hearing difficulties and in general who use very simple and effective method is sign language. This system can be used for converting sign language to text using CNN approach. An image capture system is used for sign language conversion. It captures the signs and display on the screen as writing. Results prove that the planned methodology for sign detection is more effective and has high accuracy. Experimental results will acknowledge the signs that the planned system is 80% accuracy.

Conversion in English

This subject review is an attempt to explore the notion of conversion in the English language. Conversion is commonly viewed as the use of the same root for different grammatical classes. Then, the study seeks to find out whether conversion is applicable to morphology only, to syntax only, or to both morphology and syntax. It carries out a theoretical account of the notion arriving at certain conclusions.

Analysis and Evaluation of Braille to Text Conversion Methods

Technology is advancing rapidly in present times. To serve as a useful and connected part of the community, everyone is required to learn and update themselves on innovations. Visually impaired people fall behind in this regard because of their inherent limitations. To involve these people as active participants within communities, technology must be modified for their facilitation. This paper provides a comprehensive survey of various user input schemes designed for the visually impaired for Braille to natural language conversion. These techniques are analyzed in detail with a focus on their accessibility and usability. Currently, considerable effort has been made to design a touch-screen input mechanism for visually impaired people, such as Braille Touch, Braille Enter, and Edge Braille. All of these schemes use location-specific input and challenge visually impaired persons to locate specified places on the touch screen. Most of the schemes require special actions to switch between upper and lowercase and between numbers and special characters, which affects system usability. The key features used for accessing the performance of these techniques are efficiency, accuracy, and usability issues found in the applications. In the end, a comparison of all these techniques is performed. Outcomes of this analysis show that there is a strong need for application that put the least burden on the visually impaired users. Based on this survey, a guideline has been designed for future research in this area.

Research on the Features of British and American Literary Works from Linguistic Perspective

When translating the language of British and American narrative literature, we must not only have a grasp of the language content of literary works, but also consider the differences between Chinese and English cultures. The two are to be effectively merged. If the two are separated for language processing, then the problem of language conversion will occur, and the intention and theme of the work cannot be truly reflected.

TF-IDF Inspired Detection for Cross-Language Source Code Plagiarism and Collusion

Several computing courses allow students to choose which programming language they want to use for completing a programming task. This can lead to cross-language code plagiarism and collusion, in which the copied code file is rewritten in another programming language. In response to that, this paper proposes a detection technique which is able to accurately compare code files written in various programming languages, but with limited effort in accommodating such languages at development stage. The only language-dependent feature used in the technique is source code tokeniser and no code conversion is applied. The impact of coincidental similarity is reduced by applying a TF-IDF inspired weighting, in which rare matches are prioritised. Our evaluation shows that the technique outperforms common techniques in academia for handling language conversion disguises. Further, it is comparable to those techniques when dealing with conventional disguises.