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ON CREATION of DOGRI LANGUAGE CORPUS 1Sonam Gandotra, 2Bhavna Arora 1Ph.D, Department of Computer Science & IT, Central University of Jammu

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ON CREATION of DOGRI LANGUAGE CORPUS 1Sonam Gandotra, 2Bhavna Arora 1Ph.D, Department of Computer Science & IT, Central University of Jammu JOURNAL OF CRITICAL REVIEWS ISSN- 2394-5125 VOL 7, ISSUE 09, 2020 ON CREATION OF DOGRI LANGUAGE CORPUS 1Sonam Gandotra, 2Bhavna Arora 1Ph.D, Department of Computer Science & IT, Central University of Jammu. 2Assistant Professor, Department of Computer Science & IT, Central University of Jammu AbstractThe pre-requisite for any Natural Language Processing (NLP) task, is the corpus. Corpus is defined as a large collection of structured text. Dogri is one of the official languages of India but is under-resourced in terms of computational resources needed for any NLP task. This paper proposes a methodology to construct a standard corpus which can be used for performing various language processing tasks like stemming, part-of-speech tagging, information retrieval, etc. The digitized text required for creating the corpus is not available due to the scarcity of online resources containing Dogri text. The only online source which is available is the Dogri Newspaper “Jammu Prabhat". Hence, the text is to be extracted from portable document formats (pdf) of that newspaper which are first converted to images before extraction of the text. To achieve this, an open-source tool-Tesseract is used for extracting the text from images. The methodology that is used for the corpus creation of Dogri Language is discussed in detail in the paper. The challenges faced during the research and the acquired results have also been discussed. Index Terms— Corpus, Tesseract-OCR, Dogri Language, Language Resource. In India, there are 22 official languages as defined in I. INTRODUCTION1 the eighth schedule of the Indian Constitution [9] and L ANGUAGEis one of the fundamental traits of human Dogri language being one of them. Dogri language behavior which enable us to express and communicate belongs to the class of Indo-Aryan languages, which is with people across the world. It can either be in spoken or spoken by about 5 million people in India and Pakistan written form [1]. With the advancement in technology, the but mostly has its dominance in the state of Jammu & researchers are trying to build tools which can understand Kashmir and parts of Himachal Pradesh and northern the natural language and make technology more Punjab [10]. Dogri was originally written using the Dogri accessible to the people. Natural Language Processing script [11] which has its resemblance with the Takri (NLP) has been an active area of research with the script, the script of royals of Himachal Region but now objective of making computer able to process, understand, the language is written using Devanagari script. Dogri summarize, translate and draw inferences from the human language is still in its developing form, as it has not been natural text and language. Various linguistic resources are widely explored in area of computational linguistic and required for carrying out diverse NLP tasks like machine natural language processing. Thus, resulting in scarcity of translation, automatic text summarization, sentiment online resources required for the processing of text. analysis, named entity recognition, parsing etc. These Dogri is the native language of the people of J&K and linguistic resources mainly deal with processing of text in in particular of the people of Jammu region. The written form i.e. performing processes like tokenization, digitization of this language for the creation of corpus is stemming, parsing etc. Due to progression in research taken up as the researcher itself hails from this region. In wide number of languages are being digitalized and this era of digitalization, it is important to take up every efficient tools has been developed for them[2]–[5]. But as minor step which will bring the smaller of the part in race far as Indian languages are concerned, it is still in its with the global forum. The creation of Dogri corpus will progressive phase due to the variability of the Indian lead more researchers being able to develop the NLP tools languages and their complex structure. The linguistic for Dogri language which will further enhance the resources required for the development of tools required research for the language. for processing in NLP are also limited. Researchers are Corpus is defined as the large collection of data which constantly working on providing the basic tools required can either be in written or spoken form. It is machine- for the processing of text in digital form so that better readable and is used for the purpose of linguistic research. results could be achieved [6]–[8]. A standard corpus is required for the development of tools needed for the processing of language. There are various benchmark corpuses which researchers use for executing 2337 JOURNAL OF CRITICAL REVIEWS ISSN- 2394-5125 VOL 7, ISSUE 09, 2020 NLP tasks in different domains like Brown Corpus[12], II. BACKGROUND DUC (Document Understanding Conferences) [13], TAC The task of identification of corpus or to get the corpus (Text Analysis Conference)[14], CNN dataset, Reuters in digitised form is not a challenge anymore for the dataset etc. These corpuses contain tokens, human common languages having widespread usage and generated abstractive as well as extractive summaries implementation. As large numbers of resources are freely required for evaluation of the proposed summarization available and now the researchers are concentrating on technique. These can be used for both single and multi- making improvements in the techniques which can be document summarization. These datasets are mainly applied further to enhance the quality of research. Under- developed for English, Chinese and other European resourced languages are deprived from these basic languages. As far as Indian languages are concerned, resources like: corpus, annotators, part of speech tagger, Indian languages are less explored as compared to the stemmer, named-entity lists etc. These resources provide foreign languages due to the lack of availability of a base for developing efficient tools and applications resources required for processing the text. This scenario is which boost NLP research. Over the years the researchers changing rapidly through the efforts of the researcher’s have developed tools and techniques for extracting text community, as various linguistic resources are being from the images. The researchers are also working for developed which are at par with the resources developed developing the basic resources for the under-resourced for foreign languages. Few examples of resources for text languages. A few of these tools and the basic resources are Parallel Corpora, Ontology & Word-Net, Online are discussed below as: Vishavkosh, Text Corpora etc. [15], [16] and for speech In an attempt of using Tesseract-OCR, Kumar [20] are Speech Corpora, Semi-automatic annotation tool for have used Tesseract-OCR for recognizing Gujarati Speech Corpora [17]. characters. An already available trained Gujarati script This paper aims at developing a corpus for Dogri was used for training the OCR. The results have been language. The created corpus contains news items checked by using different font-size, font style etc. and covering the domain of sports, education, politics, the mean confidence come out to be 86%. Various neural entertainment from the only Dogri newspaper “Jammu network techniques have been proposed by the Prabhat” [18]. The idea behind choosing the newspaper is researchers for identification of text from the images. to cover maximum words from all the domains. As the Word level script has been identified with the help of an data is not available in digital form and the only available end-to-end Recurrent Neural Network (RNN) based resource are the images of the text. Thus, in this work, an architecture which is able to detect and recognize the open source tool i.e. Tesseract [19] is used for extracting script and text of 12 Indian languages by Mathew in [21]. the text and making a corpus from the available resources. Two RNN structure was used each containing 3 levels of The paper begins with the introduction of the linguistic 50 Long Short-Term Memory (LSTM) nodes; one RNN is resources required for performing NLP tasks. A brief used for script identification and the other is used for introduction of Dogri language along with the status of recognition. Smitha [22] has described the whole process on-going research in the field of NLP for Dogri language of extraction of text from the document images. The is presented in Section I. The background work that has process is executed with the combination of Tesseract- been carried out previously for under-resourced languages OCR and imagemagick and then the results are compared and the different techniques used by researchers to extract with that of OCRopus.OCRopus is also an open source text from images are also discussed in Section II. In OCR developed for English language. But the results of Section III, the proposed methodology for creation of the Tesseract-OCR and imagemagick combination are Dogri corpus and the need for its development are also more promising as compared to the OCRopus. described. Section IV gives a detailed explanation of the Sankaran in paper [23] has proposed a recognition methodology for corpus creation. The challenges which system for Devanagari script using RNN known as were faced during creation of the corpus are presented in Bidirectional Long Short-Term Memory (BLSTM). The Section V. Then, the paper discusses the statistics which approach used by the author has eliminated the need for were obtained during extraction of text from the word to character segmentation thus reducing the word newspaper and book pdf in Section VI. Finally, the paper error rate by 20% and the character error rate by 9% as concludes in Section VII along with the open challenges compared to the best OCR available for the Devanagari for further research in this area are also stated. script. In [24], Chakraborty has developed a system for the visually-impaired person in which the text from the 2338 JOURNAL OF CRITICAL REVIEWS ISSN- 2394-5125 VOL 7, ISSUE 09, 2020 images are extracted and then converted to a 6-dot cell first created the corpus from local newspaper and then Braille format.
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