A Natural Language Processing-Based Active and Interactive Platform for Accessing English Language Content and Advanced Language Learning

2011 ◽  
pp. CSP24
Author(s):  
Kemal Oflazer
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Learning ◽  
Language Processing ◽  
English Language ◽  
Language Content

scholarly journals Building natural language processing tools for Runyakitara

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Fridah Katushemererwe ◽  
Andrew Caines ◽  
Paula Buttery
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Learning ◽  
Language Processing ◽  
Primary Data ◽  
Computer Assisted ◽  
Endangered Languages ◽  
Test Case ◽  
Short Supply ◽  
Linguistic Resources

AbstractThis paper describes an endeavour to build natural language processing (NLP) tools for Runyakitara, a group of four closely related Bantu languages spoken in western Uganda. In contrast with major world languages such as English, for which corpora are comparatively abundant and NLP tools are well developed, computational linguistic resources for Runyakitara are in short supply. First therefore, we need to collect corpora for these languages, before we can proceed to the design of a spell-checker, grammar-checker and applications for computer-assisted language learning (CALL). We explain how we are collecting primary data for a new Runya Corpus of speech and writing, we outline the design of a morphological analyser, and discuss how we can use these new resources to build NLP tools. We are initially working with Runyankore–Rukiga, a closely-related pair of Runyakitara languages, and we frame our project in the context of NLP for low-resource languages, as well as CALL for the preservation of endangered languages. We put our project forward as a test case for the revitalization of endangered languages through education and technology.

A Hindi Image Caption Generation Framework Using Deep Learning

2021 ◽  
Vol 20 (2) ◽  
pp. 1-19
Author(s):  
Santosh Kumar Mishra ◽  
Rijul Dhir ◽  
Sriparna Saha ◽  
Pushpak Bhattacharyya
Keyword(s):  
Computer Vision ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Image Captioning ◽  
Textual Description ◽  
Proposed Model ◽  
Hindi Language ◽  
The Given

Image captioning is the process of generating a textual description of an image that aims to describe the salient parts of the given image. It is an important problem, as it involves computer vision and natural language processing, where computer vision is used for understanding images, and natural language processing is used for language modeling. A lot of works have been done for image captioning for the English language. In this article, we have developed a model for image captioning in the Hindi language. Hindi is the official language of India, and it is the fourth most spoken language in the world, spoken in India and South Asia. To the best of our knowledge, this is the first attempt to generate image captions in the Hindi language. A dataset is manually created by translating well known MSCOCO dataset from English to Hindi. Finally, different types of attention-based architectures are developed for image captioning in the Hindi language. These attention mechanisms are new for the Hindi language, as those have never been used for the Hindi language. The obtained results of the proposed model are compared with several baselines in terms of BLEU scores, and the results show that our model performs better than others. Manual evaluation of the obtained captions in terms of adequacy and fluency also reveals the effectiveness of our proposed approach. Availability of resources : The codes of the article are available at https://github.com/santosh1821cs03/Image_Captioning_Hindi_Language ; The dataset will be made available: http://www.iitp.ac.in/∼ai-nlp-ml/resources.html .

A Framework for the Generation of Class Diagram from Text Requirements using Natural language Processing

2021 ◽  
Vol 10 (1) ◽  
pp. 25-31
Keyword(s):  
Natural Language Processing ◽  
Software Development ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Software Requirements ◽  
Class Diagram ◽  
Requirement Analysis ◽  
Part Of Speech ◽  
Software Engineers

The software development procedure begins with identifying the requirement analysis. The process levels of the requirements start from analysing the requirements to sketch the design of the program, which is very critical work for programmers and software engineers. Moreover, many errors will happen during the requirement analysis cycle transferring to other stages, which leads to the high cost of the process more than the initial specified process. The reason behind this is because of the specifications of software requirements created in the natural language. To minimize these errors, we can transfer the software requirements to the computerized form by the UML diagram. To overcome this, a device has been designed, which plans can provide semi-automatized aid for designers to provide UML class version from software program specifications using natural Language Processing techniques. The proposed technique outlines the class diagram in a well-known configuration and additionally facts out the relationship between instructions. In this research, we propose to enhance the procedure of producing the UML diagrams by utilizing the Natural Language, which will help the software development to analyze the software requirements with fewer errors and efficient way. The proposed approach will use the parser analyze and Part of Speech (POS) tagger to analyze the user requirements entered by the user in the English language. Then, extract the verbs and phrases, etc. in the user text. The obtained results showed that the proposed method got better results in comparison with other methods published in the literature. The proposed method gave a better analysis of the given requirements and better diagrams presentation, which can help the software engineers. Key words: Part of Speech,UM

scholarly journals Towards equivalence links between senses in plWordNet and Princeton WordNet

2017 ◽  
Vol 13 (1) ◽  
Author(s):  
Ewa Rudnicka ◽  
Francis Bond ◽  
Łukasz Grabowski ◽  
Maciej Piasecki ◽  
Tadeusz Piotrowski
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Learning ◽  
Language Processing ◽  
Formal Semantic ◽  
Parallel Corpus ◽  
Bilingual Dictionaries ◽  
Application Potential ◽  
Princeton Wordnet

AbstractThe paper focuses on the issue of creating equivalence links in the domain of bilingual computational lexicography. The existing interlingual links between plWordNet and Princeton WordNet synsets (sets of synonymous lexical units – lemma and sense pairs) are re-analysed from the perspective of equivalence types as defined in traditional lexicography and translation. Special attention is paid to cognitive and translational equivalents. A proposal of mapping lexical units is presented. Three types of links are defined: super-strong equivalence, strong equivalence and weak implied equivalence. The strong equivalences have a common set of formal, semantic and usage features, with some of their values slightly loosened for strong equivalence. These will be introduced manually by trained lexicographers. The sense-mapping will partly draw on the results of the existing synset mapping. The lexicographers will analyse lists of pairs of synsets linked by interlingual relations such as synonymy, partial synonymy, hyponymy and hypernymy. They will also consult bilingual dictionaries and check translation probabilities in a parallel corpus. The results of the proposed mapping have great application potential in the area of natural language processing, translation and language learning.

scholarly journals Natural language processing tools for computer assisted language learning

2003 ◽  
Vol 17 (5) ◽  
Author(s):  
Anne Vandeventer Faltin
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Learning ◽  
Language Processing ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Sentence Structure ◽  
Error Diagnosis ◽  
Diagnosis System ◽  
Spell Checker

This paper illustrates the usefulness of natural language processing (NLP) tools for computer assisted language learning (CALL) through the presentation of three NLP tools integrated within a CALL software for French. These tools are (i) a sentence structure viewer; (ii) an error diagnosis system; and (iii) a conjugation tool. The sentence structure viewer helps language learners grasp the structure of a sentence, by providing lexical and grammatical information. This information is derived from a deep syntactic analysis. Two different outputs are presented. The error diagnosis system is composed of a spell checker, a grammar checker, and a coherence checker. The spell checker makes use of alpha-codes, phonological reinterpretation, and some ad hoc rules to provide correction proposals. The grammar checker employs constraint relaxation and phonological reinterpretation as diagnosis techniques. The coherence checker compares the underlying "semantic" structures of a stored answer and of the learners' input to detect semantic discrepancies. The conjugation tool is a resource with enhanced capabilities when put on an electronic format, enabling searches from inflected and ambiguous verb forms.

scholarly journals Natural Language to SQL query Generation

2021 ◽  
Vol 9 (VI) ◽  
pp. 5069-5072
Author(s):  
Kiran Raj R
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Regular Expression ◽  
Parts Of Speech ◽  
Query Generation ◽  
Sql Query ◽  
Speech Tagging ◽  
The Web

Today, everyone has a personal device to access the web. Every user tries to access the knowledge that they require through internet. Most of the knowledge is within the sort of a database. A user with limited knowledge of database will have difficulty in accessing the data in the database. Hence, there’s a requirement for a system that permits the users to access the knowledge within the database. The proposed method is to develop a system where the input be a natural language and receive an SQL query which is used to access the database and retrieve the information with ease. Tokenization, parts-of-speech tagging, lemmatization, parsing and mapping are the steps involved in the process. The project proposed would give a view of using of Natural Language Processing (NLP) and mapping the query in accordance with regular expression in English language to SQL.

scholarly journals Associating Automatic Natural Language Processing to Serious Games and Virtual Worlds

2011 ◽  
Vol 4 (3) ◽  
Author(s):  
Treveur Bretaudière ◽  
Samuel Cruz-Lara ◽  
Lina María Rojas Barahona
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Learning ◽  
Language Processing ◽  
Virtual Worlds ◽  
Serious Games ◽  
Emotion Detection ◽  
Language Generation ◽  
Research Activities ◽  
Information Framework

We present our current research activities associating automatic natural language processing to serious games and virtual worlds. Several interesting scenarios have been developed: language learning, natural language generation, multilingual information, emotion detection, real-time translations, and non-intrusive access to linguistic information such as definitions or synonyms. Part of our work has contributed to the specification of the Multi Lingual Information Framework [ISO FDIS 24616], (MLIF,2011). Standardization will grant stability,  interoperability and sustainability of an important part of our research activities, in particular, in the framework of representing and managing multilingual textual information.

Supporting the Translation and Authoring of Test Items with Techniques of Natural Language Processing

2008 ◽  
Vol 12 (3) ◽  
pp. 234-242
Author(s):  
Ming-Shin Lu ◽  
◽  
Yu-Chun Wang ◽  
Jen-Hsiang Lin ◽  
Chao-Lin Liu ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Learning ◽  
Language Processing ◽  
Test Item ◽  
Software Systems ◽  
Software Environment ◽  
Test Items ◽  
Important Field ◽  
Mathematics And Science

Using techniques of natural language processing to assist the preparation of educational resources for language learning has become an important field. We report two software systems that are designed for assisting the tasks of test item translation and test item authoring. We built a software environment to help experts translate the test items for the Trends in International Mathematics and Science Study (TIMSS). Test items of TIMSS are prepared in American English and will be translated to traditional Chinese. We also built a software environment for composing test items for introductory Chinese courses. The system currently aids the preparation of four important categories of test items, and the resulting test items can be administrated on the Internet.

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