International Journal on Natural Language Computing (IJNLC)

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Natural Language Processing is a programmed approach to analyze text that is based on both a set of theories and a set of technologies. This forum aims to bring together researchers who have designed and build software that will analyze, understand, and generate languages that humans use naturally to address computers.

International Journal on Natural Language Computing (IJNLC)
ISSN: 2278 - 1307 [Online]; 2319 - 4111 [Print]
http://airccse.org/journal/ijnlc/index.html
*** H-index 16, i10-index 25 ***
Scope & Topics
Natural Language Processing is a programmed approach to analyze text that is based on both a
set of theories and a set of technologies. This forum aims to bring together researchers who have
designed and build software that will analyze, understand, and generate languages that humans
use naturally to address computers.
Topics of interest include but are not limited to, the following
 Phonology, Morphology
 Chunking/Shallow Parsing
 Parsing/Grammatical Formalisms
 Semantic Processing
 Lexical Semantics
 Ontology
 Linguistic Resources
 Statistical and Knowledge based methods
 POS tagging
 Discourse
 Paraphrasing/Entailment/Generation
 Machine Translation
 Information Retrieval
 Text Mining
 Information Extraction
 Question Answering
 Dialog Systems
 Spoken Language Processing
 Speech Recognition and Synthesis
Paper Submission
Authors are invited to submit papers for this journal through E-mail: ijnlcjournal@airccse.org.
Submissions must be original and should not have been published previously or be under
consideration for publication while being evaluated for this Journal.
Important Dates
 Submission Deadline : May 30, 2020
 Notification : June 30, 2020
 Final Manuscript Due : July 08, 2020
 Publication Date : Determined by the Editor-in-Chief
For other details please visit http://airccse.org/journal/ijnlc/index.html

Contact Us
Here's where you can reach us: ijnlcjournal@airccse.org
Submission Link: http://coneco2009.com/submissions/imagination/home.html

The International Journal on Natural Language Computing (IJNLC) aims to bring together researchers working on analyzing, understanding, and generating human languages using computational techniques. The journal covers topics related to natural language processing including phonology, morphology, parsing, semantics, machine translation, information retrieval, question answering, and spoken language processing. It invites authors to submit original papers by April 25, 2020 for peer review and plans to publish accepted papers starting in June 2020.

International Journal on Natural Language Computing (IJNLC)

kevig

International journal on natural language computing(ijnlc)

kevig

Com ling

Mohammad Raza

The document discusses the field of computational linguistics. It defines computational linguistics as the scientific study of language from a computational perspective, involving linguists, computer scientists, and others. The history of computational linguistics is closely tied to the development of digital computers and early applications included machine translation. Computational linguistics research includes areas like speech recognition, natural language processing, and machine translation.

Lit mtap

Andrea Ferracani

LIT (Lexicon of the Italian Television) is a project conceived by the Accademia della Crusca, the leading research institution on the Italian language, in collaboration with CLIEO (Center for theoretical and historical Linguistics: Italian, European and Oriental languages), with the aim of studying frequencies of the Italian lexicon used in television content and targets the specific sector of web applications for linguistic research. The corpus of transcriptions is constituted approximately by 170 hours of random television recordings transmitted by the national broadcaster RAI (Italian Radio Television) during the year 2006.

Learning and Text Analysis for Ontology Engineering

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This document calls for papers and participation in a workshop on learning and text analysis for ontology engineering to be held in conjunction with the ECAI 2002 conference in Lyon, France. The workshop aims to bring together researchers from linguistics, natural language processing, knowledge representation, and machine learning to discuss issues around building, maintaining, and reusing ontologies and terminological resources. Topics of interest include using texts and linguistic/terminological resources as knowledge sources for building ontologies, applying machine learning and NLP tools to ontology engineering, and learning ontologies from sources like the web. The deadline for paper submissions is March 15th and for motivation abstracts is May 24th. The workshop will include paper presentations, discussions, and

1 computational linguistics an introduction

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The document discusses the field of computational linguistics, defining it as the scientific study of language from a computational perspective. It involves providing computational models of linguistic phenomena and using computational techniques and linguistic theories to solve problems in natural language processing. Computational linguistics aims to automatically process and understand natural language by constructing computer programs. The field has its roots in the 1940s-1950s with the development of code breaking machines and computers. Major conferences and journals in the field are associated with the Association for Computational Linguistics.

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This document discusses computational linguistics, including its origins, main application areas, and approaches. Computational linguistics originated from efforts in the 1950s to use computers for machine translation between languages. It aims to develop natural language processing applications like machine translation, speech recognition, and grammar checking. Research employs various approaches including developmental, structural, production-focused, and comprehension-focused methods. The field involves both computer science and linguistics.

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The process of identification of Named Entities (NEs) in a given document and then there classification into different categories of NEs is referred to as Named Entity Recognition (NER). We need to do a great effort in order to perform NER in Indian languages and achieve the same or higher accuracy as that obtained by English and the European languages. In this paper, we have presented the results that we have achieved by performing NER in Hindi, Bengali and Telugu using Hidden Markov Model (HMM) and Performance Metrics.

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Query in a search engine is generally based on natural language. A query can be expressed in more than one way without changing its meaning as it depends on thinking of human being at a particular moment. Aim of the searcher is to get most relevant results immaterial of how the query has been expressed. In the present paper, we have examined the results of search engine for change in coverage and similarity of first few results when a query is entered in two semantically same but in different formats. Searching has been made through Google search engine. Fifteen pairs of queries have been chosen for the study. The t-test has been used for the purpose and the results have been checked on the basis of total documents found, similarity of first five and first ten documents found in the results of a query entered in two different formats. It has been found that the total coverage is same but first few results are significantly different.

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Speech generation is one of the most important areas of research in speech signal processing which is now gaining a serious attention. Speech is a natural form of communication in all living things. Computers with the ability to understand speech and speak with a human like voice are expected to contribute to the development of more natural man-machine interface. However, in order to give those functions that are even closer to those of human beings, we must learn more about the mechanisms by which speech is produced and perceived, and develop speech information processing technologies that can generate a more natural sounding systems. The so described field of stud, also called speech synthesis and more prominently acknowledged as text-to-speech synthesis, originated in the mid eighties because of the emergence of DSP and the rapid advancement of VLSI techniques. To understand this field of speech, it is necessary to understand the basic theory of speech production. Every language has different phonetic alphabets and a different set of possible phonemes and their combinations. For the analysis of the speech signal, we have carried out the recording of five speakers in Dogri (3 male and 5 females) and eight speakers in Hindi language (4 male and 4 female). For estimating the durational distributions, the mean of mean of ten instances of vowels of each speaker in both the languages has been calculated. Investigations have shown that the two durational distributions differ significantly with respect to mean and standard deviation. The duration of phoneme is speaker dependent. The whole investigation can be concluded with the end result that almost all the Dogri phonemes have shorter duration, in comparison to Hindi phonemes. The period in milli seconds of same phonemes when uttered in Hindi were found to be longer compared to when they were spoken by a person with Dogri as his mother tongue. There are many applications which are directly of indirectly related to the research being carried out. For instance the main application may be for transforming Dogri speech into Hindi and vice versa, and further utilizing this application, we can develop a speech aid to teach Dogri to children. The results may also be useful for synthesizing the phonemes of Dogri using the parameters of the phonemes of Hindi and for building large vocabulary speech recognition systems.

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International Journal on Natural Language Computing (IJNLC)

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In recent years, great advances have been made in the speed, accuracy, and coverage of automatic word sense disambiguator systems that, given a word appearing in a certain context, can identify the sense of that word. In this paper we consider the problem of deciding whether same words contained in different documents are related to the same meaning or are homonyms. Our goal is to improve the estimate of the similarity of documents in which some words may be used with different meanings. We present three new strategies for solving this problem, which are used to filter out homonyms from the similarity computation. Two of them are intrinsically non-semantic, whereas the other one has a semantic flavor and can also be applied to word sense disambiguation. The three strategies have been embedded in an article document recommendation system that one of the most important Italian ad-serving companies offers to its customers.

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Machine Transliteration has come out to be an emerging and a very important research area in the field of machine translation. Transliteration basically aims to preserve the phonological structure of words. Proper transliteration of name entities plays a very significant role in improving the quality of machine translation. In this paper we are doing machine transliteration for English-Punjabi language pair using rule based approach. We have constructed some rules for syllabification. Syllabification is the process to extract or separate the syllable from the words. In this we are calculating the probabilities for name entities (Proper names and location). For those words which do not come under the category of name entities, separate probabilities are being calculated by using relative frequency through a statistical machine translation toolkit known as MOSES. Using these probabilities we are transliterating our input text from English to Punjabi.

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The popularity of functional foods among scientists and common people has been increasing day by day. Awareness and modernization make the consumer think better regarding food and nutrition. Now a day’s individual knows very well about the relation between food consumption and disease prevalence. Humans have a diversity of microbes in the gut that together form the gut microflora. Probiotics are the health-promoting live microbial cells improve host health through gut and brain connection and fighting against harmful bacteria. Bifidobacterium and Lactobacillus are the two bacterial genera which are considered to be probiotic. These good bacteria are facing challenges of viability. There are so many factors such as sensitivity to heat, pH, acidity, osmotic effect, mechanical shear, chemical components, freezing and storage time as well which affects the viability of probiotics in the dairy food matrix as well as in the gut. Multiple efforts have been done in the past and ongoing in present for these beneficial microbial population stability until their destination in the gut. One of a useful technique known as microencapsulation makes the probiotic effective in the diversified conditions and maintain these microbe’s community to the optimum level for achieving targeted benefits. Dairy products are found to be an ideal vehicle for probiotic incorporation. It has been seen that the encapsulated microbial cells show higher viability than the free cells in different processing and storage conditions as well as against bile salts in the gut. They make the food functional when incorporated, without affecting the product sensory characteristics.

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International Journal on Natural Language Computing (IJNLC)

1. International Journal on Natural Language Computing (IJNLC) ISSN: 2278 - 1307 [Online]; 2319 - 4111 [Print] http://airccse.org/journal/ijnlc/index.html *** H-index 16, i10-index 25 *** Scope & Topics Natural Language Processing is a programmed approach to analyze text that is based on both a set of theories and a set of technologies. This forum aims to bring together researchers who have designed and build software that will analyze, understand, and generate languages that humans use naturally to address computers. Topics of interest include but are not limited to, the following  Phonology, Morphology  Chunking/Shallow Parsing  Parsing/Grammatical Formalisms  Semantic Processing  Lexical Semantics  Ontology  Linguistic Resources  Statistical and Knowledge based methods  POS tagging  Discourse  Paraphrasing/Entailment/Generation  Machine Translation  Information Retrieval  Text Mining  Information Extraction  Question Answering  Dialog Systems  Spoken Language Processing  Speech Recognition and Synthesis Paper Submission Authors are invited to submit papers for this journal through E-mail: ijnlcjournal@airccse.org. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. Important Dates  Submission Deadline : May 30, 2020  Notification : June 30, 2020  Final Manuscript Due : July 08, 2020  Publication Date : Determined by the Editor-in-Chief For other details please visit http://airccse.org/journal/ijnlc/index.html

2. Contact Us Here's where you can reach us: ijnlcjournal@airccse.org Submission Link: http://coneco2009.com/submissions/imagination/home.html

International Journal on Natural Language Computing (IJNLC)

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