scholarly journals Identification of language in a cross linguistic environment

2020 ◽  
Vol 18 (1) ◽  
pp. 544
Author(s):  
Merin Thomas ◽  
Dr Latha C A ◽  
Antony Puthussery
Keyword(s):  
Native Language ◽  
Indian Languages ◽  
Algorithmic Approach ◽  
South Indian ◽  
The Social ◽  
Social Media Text ◽  
Cross Lingual ◽  
Multiple Languages ◽  
Day By Day ◽  
Indian Scenario

<p class="normal">World has become very small due to software internationationalism. Applications of machine translations are increasing day by day. Using multiple languages in the social media text is an developing trend. .Availability of   fonts in the native language enhanced the usage of native text in internet communications. Usage of   transliterations of language   has become quite common. In Indian scenario current generations are   familiar to talk in native language but not to read and write in the native language, hence they started using English representation of native language in textual messages. This paper describes the   identification of the transliterated text in cross lingual environment .In this paper a Neural network model   identifies the prominent language in the text and hence the same can be used to identify the meaning of the text in the concerned language. The model is based upon Recurrent Neural Networks that found to be the most efficient in machine translations. Language identification can serve as a base for many applications in multi linguistic environment. Currently the South Indian Languages Malayalam, Tamil are identified from given text. An algorithmic approach of Stop words based model is depicted in this paper. Model can be also enhanced to address all the Indian Languages that are in use.</p>

CSR@ 2%: A NEW MODEL OF CORPORATE SOCIAL RESPONSIBILITY IN INDIA

2018 ◽  
Vol 1 (3) ◽  
pp. 56-66
Author(s):  
Anupam Singh ◽  
Dr. Priyanka Verma
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Corporate Philanthropy ◽  
Social Issues ◽  
Business Community ◽  
Net Worth ◽  
The Social ◽  
Net Profit ◽  
Corporate Social ◽  
Indian Scenario

Corporate Social Responsibility (CSR) earlier applied as corporate philanthropy and has been in practice in India since ages. However, philanthropy in globalised and modern India does not solve the purpose in quantity and quality. Clause 135 of Company Act 2013 created huge hue and cry among the business community in India. As per clause 135 of the Companies Act, 2013, Every company with an annual turnover of 1,000 crore INR ($161 million) and more, or a net worth of 500 crore INR ($80 million) and more, or a net profit as low as five crore INR ($800,000) and more have to spend at least 2% of their average net profit over the previous three years on CSR activities. With the introduction of new Company act 2013 India became the first country in the world to have legislation for compulsory CSR spending. The paper aims at analyzing the motive of making CSR spending mandatory and it also attempts to explain the concept of CSR in the present Indian scenario, the social issues addressed by the Indian corporations, and methodologies adopted by them to address those issues.

Cross-lingual voice conversion-based polyglot speech synthesizer for indian languages

2014 ◽  
Author(s):  
B. Ramani ◽  
M. P. Actlin Jeeva ◽  
P. Vijayalakshmi ◽  
T. Nagarajan
Keyword(s):  
Voice Conversion ◽  
Indian Languages ◽  
Speech Synthesizer ◽  
Cross Lingual

Spam Detection on Social Media Using Semantic Convolutional Neural Network

2018 ◽  
Vol 8 (1) ◽  
pp. 12-26 ◽  
Author(s):  
Gauri Jain ◽  
Manisha Sharma ◽  
Basant Agarwal
Keyword(s):  
Neural Network ◽  
Social Media ◽  
Convolutional Neural Network ◽  
State Of The Art ◽  
Spam Detection ◽  
Learning Technology ◽  
The Social ◽  
Social Media Text ◽  
Current Article ◽  
Semantic Layer

This article describes how spam detection in the social media text is becoming increasing important because of the exponential increase in the spam volume over the network. It is challenging, especially in case of text within the limited number of characters. Effective spam detection requires more number of efficient features to be learned. In the current article, the use of a deep learning technology known as a convolutional neural network (CNN) is proposed for spam detection with an added semantic layer on the top of it. The resultant model is known as a semantic convolutional neural network (SCNN). A semantic layer is composed of training the random word vectors with the help of Word2vec to get the semantically enriched word embedding. WordNet and ConceptNet are used to find the word similar to a given word, in case it is missing in the word2vec. The architecture is evaluated on two corpora: SMS Spam dataset (UCI repository) and Twitter dataset (Tweets scrapped from public live tweets). The authors' approach outperforms the-state-of-the-art results with 98.65% accuracy on SMS spam dataset and 94.40% accuracy on Twitter dataset.

scholarly journals Poder, sexo e línguas no marxismo à brasileira

2019 ◽  
Vol 16 (31) ◽  
pp. 131
Author(s):  
Lidiane Soares Rodrigues
Keyword(s):  
Social Sciences ◽  
Foreign Language ◽  
Competitive Advantage ◽  
Social Space ◽  
Native Language ◽  
Linguistic Capital ◽  
The Social ◽  
The Asymmetry

Em sondagem realizada junto a marxistas brasileiros, as principais filiações distribuíram-se do seguinte modo: Gramsci(nianos) reuniu 33,2% da população; Lukács(ianos), 25,8%; Escola de Frankfurt(ianos), 10,5% e Althusser(ianos), 7,2%. A mesma sondagem indagou a fluência em língua estrangeira, obtendo respostas para: espanhol, de 49% da população; para inglês, de 46,0%; para francês, de 20%; para italiano, de 8% e, para alemão, de 2,9% (a cifra de 26% declarou não ter fluência em idioma estrangeiro). É notável que a língua nativa dos autores não corresponda à língua estrangeira de mais domínio dos marxistas (por exemplo, enquanto 33,2% são gramscinianos; apenas 8% declaram-se fluentes em italiano). Esta decalagem indica que o domínio da língua nativa dos autores de filiação consiste num recurso diferencial que confere vantagens  competitivas aos agentes. O presente artigo tratará dos efeitos da assimetria de capital linguístico no espaço social dos marxistas brasileiros.Palavras-chave: Marxismo. Ciências  sociais brasileiras. Capital linguístico.Power, sex and languages among brazilian marxistsAbstractIn a survey of Brazilian Marxists, the main affiliations were distributed as follows:-Gramsci(nianos) gathered 33.2% of the population; Lukács(ianos), 25.8%; Frankfurt(ianos) School, 10.5% and Althusser(ianos), 7.2%. The same survey asked for fluency in a foreign language, obtaining answers for: Spanish, 49% of the population; English, 46.0%; French, 20%; Italian, 8%; and German, 2.9% (the figure of 26% declared to have no fluency in a foreign language). It is notable that the native language of the authors does not correspond to the foreign language most spoken by Marxists (for example, while 33.2% are gramscinese; only 8% are fluent in Italian).This difference indicates that mastery of the native language of the authors of affiliation is a differential resource which gives a competitive advantage to the agents. This article will deal with the effects of the asymmetry of linguistic capital on the social space of Brazilian Marxists.Keywords: Marxism. Brazilian Social sciences. linguistic capital.

Cross-Lingual Information Retrieval

2005 ◽  
pp. 153-170 ◽  
Author(s):  
Christopher Yang ◽  
Kar W. Li
Keyword(s):  
Information Retrieval ◽  
Digital Library ◽  
Digital Libraries ◽  
World Wide ◽  
Relevant Information ◽  
Semantic Interoperability ◽  
Library Research ◽  
The World ◽  
Cross Lingual ◽  
Multiple Languages

Structural and semantic interoperability have been the focus of digital library research in the early 1990s. Many research works have been done on searching and retrieving objects across variations in protocols, formats, and disciplines. As the World Wide Web has become more popular in the last ten years, information is available in multiple languages in global digital libraries. Users are searching across the language boundary to identify the relevant information that may not be available in their own language. Cross-lingual semantic interoperability has become one of the focuses in digital library research in the late 1990s. In particular, research in cross-lingual information retrieval (CLIR) has been very active in recent conferences on information retrieval, digital libraries, knowledge management, and information systems. The major problem in CLIR is how to build the bridge between the representations of user queries and documents if they are of different languages.

Location-Based Internationalization and Localization With Mobile Computing

2022 ◽  
pp. 39-58
Author(s):  
Arpit Kumar Sharma ◽  
Arvind Dhaka ◽  
Amita Nandal ◽  
Akshat Sinha ◽  
Deepika Choudhary
Keyword(s):  
Mobile Computing ◽  
Native Language ◽  
Android Application ◽  
Location Data ◽  
Web Tools ◽  
Dead End ◽  
Static Data ◽  
Android System ◽  
Multiple Languages

The Android system operates on many smartphones in many locales. Websites and web tools have their own requirements in day-to-day life. To reach the maximum users, the app and website should handle all the resources such as text strings, functions, layouts, graphics, and any other static data that the app/website needs. It requires internationalization and localization of the website and app to support multiple languages. The basic idea of this chapter is to present an approach for localizing the Android application according to the location data that the app received from the device, but many users do not allow the “access location” feature so this approach will be a dead end in this case. The authors have proposed some other techniques to achieve this feature of localization and internationalization by implementing the “choose language” service so that the app can itself optimize its content and translate it into the user's native language.

A Zone Based Approach for Classification and Recognition Of Telugu Handwritten Characters

2016 ◽  
Vol 6 (4) ◽  
pp. 1647
Author(s):  
N. Shobha Rani ◽  
Sanjay Kumar Verma ◽  
Anitta Joseph
Keyword(s):  
Feature Extraction ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Vital Role ◽  
Indian Languages ◽  
Processing Application ◽  
Image Objects ◽  
South Indian ◽  
Recognition Systems ◽  
The Times

Realization of high accuracies and efficiencies in South Indian character recognition systems is one of the principle goals to be attempted time after time so as to promote the usage of optical character recognition (OCR) for South Indian languages like Telugu. The process of character recognition comprises pre-processing, segmentation, feature extraction, classification and recognition. The feature extraction stage is meant for uniquely recognizing each character image for the purpose of classifying it. The selection of a feature extraction algorithm is very critical and important for any image processing application and mostly of the times it is directly proportional to the type of the image objects that we have to identify. For optical technologies like South Indian OCR, the feature extraction technique plays a very vital role in accuracy of recognition due to the huge character sets. In this work we mainly focus on evaluating the performance of various feature extraction techniques with respect to Telugu character recognition systems and analyze its efficiencies and accuracies in recognition of Telugu character set.

Indigenous Metaphors and the Philosophy of History in Cooper’s Leatherstocking Tales

2017 ◽  
Author(s):  
Sarah Rivett
Keyword(s):  
Native Language ◽  
James Fenimore Cooper ◽  
Indian Languages ◽  
American Continent ◽  
Aesthetic Value ◽  
Early Nineteenth Century ◽  
Anglo American ◽  
The Aesthetic ◽  
Verse Forms

Chapter 8 explores how a fascination with a “native language” emerged in literary circles through a simultaneous indebtedness to traditional British prose and verse forms, and Anglo-American linguistic affiliation with indigenous-language roots. By 1815, the “Historical and Literary Committee of the American Philosophical Society” would declare this “native language” a uniquely “American idiom” to be discovered on the American continent through the “numerous novel forms” of Indian languages. In his early novels, James Fenimore Cooper seized upon the aesthetic value that could be constructed from Indian languages and from the figure of the noble savage. I show how Cooper’s novels build upon beliefs in the prelapsarian quality of indigenous languages. I argue that the regenerative potential that Cooper’s novels portray as arising from Indian words functions as aesthetic compensation for the violence and repeated violation of treaty agreements that characterized US and Indian relations in the early nineteenth century.

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