UNL-ization of Numbers and Ordinals in Punjabi with IAN

2013

UNL-ization is the process of converting Natural Language resource to Universal Natural Language ( i.e., UNL). UNL is based on Interlingua approach, specifically designed by UNDL foundation for storing, summarizing, representing and describing information in a format which is independent to a natural language. This paper illustrates UNL-ization of Punjabi language with the help of IAN ( i.e., Interactive AN alysis) tool. UNL-ization of major part-of-speeches of a Natural language viz Preposition, Conjunction, Determiner, Verb, Noun, Adjective, Time, Numbers and Ordinals has been done. In this paper UNL-ization process is explained with the help of three example sentences. Total 257 TRules and 623 Dictionary entries have been created, and the system has been tested successfully for Corpus500 (provided by UNDL Foundation) for Five hundred Punjabi sentences, comprising of all the major part-of-speeches and its FMeasure comes out to be 0.936 (on a scale of 0 to 1).

Sadhana, 2012

This paper reports the work for the EnConversion of input Punjabi sentences to an interlingua representation called Universal Networking Language (UNL). The UNL system consists of two main components, namely, EnConverter (used for converting the text from a source language to UNL) and DeConverter (used for converting the text from UNL to a target language). This paper discusses the framework for designing the EnConverter for Punjabi language with a special focus on generation of UNL attributes and relations from Punjabi source text. It also describes the working of Punjabi Shallow Parser used for the processing of the input sentence, which performs the tasks of Tokenizer, Morph-analyzer, Part-of-Speech Tagger and Chunker. This paper also considers the seven phases used in the process of EnConversion of input Punjabi text to UNL representation. The paper highlights the EnConversion analysis rules used for the EnConverter and indicates its usage in the generation of UNL expressions. This paper also covers the results of implementation of Punjabi EnConverter and its evaluation on sample UNL sentences available at Spanish Language Server. The accuracy of the developed system has also been presented in this paper.

2014

Now a days, whatever information we receive by the website are based on computer application. Recent trends depend on E-Commerce based service. Using this application people can communicate and have an access to information. It enables us to access innumerable documents with a huge variety of topics from any place around the world. Despite abundance of information, language is a very big obstacle. When the web pages are written in different languages like English, French, Hindi, Chinese etc., it becomes difficult for a person with insufficient prerequisite knowledge of languages to access all the information. Translation of native language to another is very demandable now due to increasing the usage of web based application. Every country has its own language. Therefore, Language is very essential part for communication skill with each other. Firstly, a sentence of a language is converted to Universal Networking Language (UNL) expressions and then UNL expressions can be converted t...

Universal Networking Language (UNL) is a declarative formal language that is used to represent semantic data extracted from natural language texts. This paper presents a novel approach to converting Bangla natural language text into UNL using a method known as Predicate Preserving Parser (PPP) technique. PPP performs morphological, syntactic and semantic, and lexical analysis of text synchronously. This analysis produces a semantic-net like structure represented using UNL. We demonstrate how Bangla texts are analyzed following the PPP technique to produce UNL documents which can then be translated into any other suitable natural language facilitating the opportunity to develop a universal language translation method via UNL.

International Journal of Engineering Research and Technology (IJERT), 2012

https://www.ijert.org/natural-language-processing-approaches-application-and-limitations https://www.ijert.org/research/natural-language-processing-approaches-application-and-limitations-IJERTV1IS7481.pdf Natural language is the language which is used or spoken by the human being these languages are Hindi, English, French, Marathi, Bengali, Gujrati so on. And a natural language processing is the area of artificial intelligence and natural processing is based on creating system through which human can interact with computer in his/her own language without any problem in this paper we focus on natural language processing concept , its approaches , its types and natural language processing application.

Universal Networking Language (UNL) has been used by various researchers as an Interlingua approach for AMT (Automatic machine translation). The UNL system consists of two main components/tools, namely, EnConverter-IAN (used for converting the text from a source language to UNL) and DeConverter - EUGENE (used for converting the text from UNL to a target language). This paper highlights the DeConversion generation rules used for the DeConverter and indicates its usage in the generation of Punjabi sentences. This paper also covers the results of implementation of UNL input by using DeConverter-EUGENE and its evaluation on UNL sentences such as Nouns, Pronouns and Prepositions.

International Journal of Research in Science and Technology, 2020

India is a country having multiple languages. The states in the country are based on languages; the people speak in those regions. Even in the same state, the language changes over short distances. Indian language has multiple kinds of literaturethatare difficult for another person in different regions to understand their language. This can be a useful tool for fillingthe gap between two languages with the help of NLP. As we know, NLP is a part of AI, whichcontains computer science and sentiment or linguistics.So, we can say that NLP is a technique which works as a bridge between humans and computerto fill the gap in computer language.It requires deep knowledge of statistics, computer language, and linguistics.So, it can be placed in the multidisciplinary area. Although research is going on in this field, still the solutions produced do not provide satisfactory results. It is due to the diversity of Indian languages and other challenges like unavailability of Natural Language Processing tools, unavailability of annotated corpora, absence of standards, ambiguity in conversion, an unmatched word in target languages, etc.

2013

Unlike most user-computer interfaces, a natural language interface allows users to communicate fluently with a computer system with very little preparation. Databases are often hard to use in cooperating with the users because of their rigid interface. A good NLIDB allows a user to enter commands and ask questions in native language and then after interpreting respond to the user in native language. For a large number of applications requiring interaction between humans and the computer systems, it would be convenient to provide the end-user friendly interface. Punjabi language interface to database would proof fruitful to native people of Punjab, as it provides ease to them to use various e-governance applications like Punjab Sewa, Suwidha, Online Public Utility Forms, Online Grievance Cell, Land Records Management System,legacy matters, e-District, agriculture, etc. Punjabi is the mother tongue of more than 110 million people all around the world. According to available information, Punjabi ranks 10th from top out of a total of 6,900 languages recognized internationally by the United Nations. This paper covers a brief overview of the Natural language interface to database, its different components, its advantages, disadvantages, approaches and techniques used. The paper ends with the work done on Punjabi language interface to database and future enhancements that can be done.

Proc. V International Conf. Natural Language Processing (KBCS 2004), 2004

All areas of language and speech technology, directly or indirectly, require handling of real (unrestricted) text. For example, text-to-speech systems directly need to work on real text, whereas automatic speech recognition systems depend on language models that are trained on text. This paper reports our ongoing effort on Hindi text normalization. In that, a novel approach to text normalization, wherein tokenization and initial token classification are combined into one stage followed by a second level of token sense disambiguation, is described. Tokenization and initial token classification are performed using a lexical analyser that is derived from various token definitions in the form of regular expressions. For second level of token sense disambiguation, application of decision lists and decision trees are explored. Token-to-word rules are then applied, which are specific for each token type and also for each format within a token type.

International Journal of Information and Education Technology, 2014