scholarly journals Mood and Vulnerability Prediction through Natural Language Processing

2019 ◽  
Vol 9 (2) ◽  
pp. 1335-1345
Keyword(s):  
Language Processing ◽  
English Language ◽  
Emotional State ◽  
Research Work ◽  
Medical Treatments ◽  
Parts Of Speech ◽  
Verbal Form ◽  
User Input ◽  
Vulnerability Prediction ◽  
Processing Step

Analyzing various phases of mood using the verbal form of writing can serve as advancement in the field of psychology. The research work highlighted in this paper focuses on the use of sentiment analysis to predict the emotional state and vulnerability of written statements, as per the most generic perceptions, in the English language, with the help of an algorithm. The text pre-processing step discussed in this work involves cultivating and analyzing each word of user input, analyzing their literal and emotional essences to sum up the mood inclination of the statements and other parts-of-speech, to determine the specific mood and the vulnerability of the writing itself. The vulnerability level of the document is also determined, in order to extent out the purpose towards medical treatments where a vulnerable mindset, suffering from mental illness, depression, perceives the capability to inflict harm upon oneself or others can be given proper help and counseling.

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 Multi - Class Document Classification: Effective and Systematized Method to Categorize Documents

2020 ◽  
pp. 118-123 ◽  
Author(s):  
Kaushika Pal ◽  
Biraj V. Patel
Keyword(s):  
Machine Learning ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Nearest Neighbor ◽  
Research Work ◽  
Support Vector ◽  
Indian Languages ◽  
K Nearest Neighbor

A large section of World Wide Web is full of Documents, content; Data, Big data, unformatted data, formatted data, unstructured and unorganized data and we need information infrastructure, which is useful and easily accessible as an when required. This research work is combining approach of Natural Language Processing and Machine Learning for content-based classification of documents. Natural Language Processing is used which will divide the problem of understanding entire document at once into smaller chucks and give us only with useful tokens responsible for Feature Extraction, which is machine learning technique to create Feature Set which helps to train classifier to predict label for new document and place it at appropriate location. Machine Learning subset of Artificial Intelligence is enriched with sophisticated algorithms like Support Vector Machine, K – Nearest Neighbor, Naïve Bayes, which works well with many Indian Languages and Foreign Language content’s for classification. This Model is successful in classifying documents with more than 70% of accuracy for major Indian Languages and more than 80% accuracy for English Language.

A Comprehensive Guideline for Bengali Sentiment Annotation

2022 ◽  
Vol 21 (2) ◽  
pp. 1-19
Author(s):  
Md. Saddam Hossain Mukta ◽  
Md. Adnanul Islam ◽  
Faisal Ahamed Khan ◽  
Afjal Hossain ◽  
Shuvanon Razik ◽  
...  
Keyword(s):  
Data Mining ◽  
Information Retrieval ◽  
Sentiment Analysis ◽  
Computational Linguistics ◽  
Language Processing ◽  
Web Mining ◽  
English Language ◽  
Research Work ◽  
Bengali Language

Sentiment Analysis (SA) is a Natural Language Processing (NLP) and an Information Extraction (IE) task that primarily aims to obtain the writer’s feelings expressed in positive or negative by analyzing a large number of documents. SA is also widely studied in the fields of data mining, web mining, text mining, and information retrieval. The fundamental task in sentiment analysis is to classify the polarity of a given content as Positive, Negative, or Neutral . Although extensive research has been conducted in this area of computational linguistics, most of the research work has been carried out in the context of English language. However, Bengali sentiment expression has varying degree of sentiment labels, which can be plausibly distinct from English language. Therefore, sentiment assessment of Bengali language is undeniably important to be developed and executed properly. In sentiment analysis, the prediction potential of an automatic modeling is completely dependent on the quality of dataset annotation. Bengali sentiment annotation is a challenging task due to diversified structures (syntax) of the language and its different degrees of innate sentiments (i.e., weakly and strongly positive/negative sentiments). Thus, in this article, we propose a novel and precise guideline for the researchers, linguistic experts, and referees to annotate Bengali sentences immaculately with a view to building effective datasets for automatic sentiment prediction efficiently.

scholarly journals Advanced Tamil POS Tagger for Language Learners

2019 ◽  
Vol 8 (10) ◽  
pp. 741-745
Keyword(s):  
Machine Translation ◽  
Language Learners ◽  
Language Processing ◽  
Research Work ◽  
Important Work ◽  
Parts Of Speech ◽  
Pos Tagging ◽  
Pos Tagger ◽  
The Given ◽  
Speech Identification

In the emerging technology Natural Language Processing, machine translation is one of the important roles. The machine translation is translation of text in one language to another with the implementation of Machines. The research topic POS Tagging is one of the most basic and important work in Machine translation. POS tagging simply, we say that to assign the Parts of speech identification for each word in the given sentence. In my research work, I tried the POS Tagging for Tamil language. There may be some numerous research were done in the same topic. I have viewed this in different and very detailed implementation. Most of the detailed grammatical identifications are made for this proposed research. It is very useful to know the basic grammar in Tamil language

Research on Starvation in the Warsaw Ghetto – Ethical Problems

2010 ◽  
pp. 439-450
Author(s):  
Marta Janczewska
Keyword(s):  
Research Team ◽  
Ethical Dilemmas ◽  
Medical Profession ◽  
Research Work ◽  
Special Kind ◽  
Scientific Discipline ◽  
Medical Treatments ◽  
Warsaw Ghetto ◽  
Dying Patients ◽  
To Receive

Research team of physicians and lab technicians under Izrael Milejkowski’s direction undertook the effort to carry out a series of clinical and biochemical experiments on patients dying of starvation in the Warsaw ghetto so as to receive the fullest possible picture of hunger disease. The research was carried out according to all the rigors of strict scientific discipline, and the authors during their work on academic articles, published it after the war entitled: „Starvation disease: hunger research carried out in the Warsaw ghetto in 1942,” according to their own words, they “supplemented the gap in accordance with the progress of knowledge.” The article is devoted to the reflections over ethical dilemmas of the research team, who were forced in their work to perform numerous medical treatments of experimental nature on extremely exhausted patients. The ill, according to Dr Fajgenblat’s words,“demonstrated negativism toward the research and treatment, which extremely hindered the work, and sometimes even frustrated it.” The article attempts to look at the monumental research work of the Warsaw ghetto doctors as a special kind of response of the medical profession to the feeling of helplessness to the dying patients. The article analyzes the situation of Warsaw ghetto doctors, who undertook the research without support of any outer authority, which could settle their possible ethical dilemmas (Polish deontological codes, European discussions on the conditions of the admissibility of medical research on patients, etc.).

DEVELOPMENT OF SCIENTIFIC AND RESEARCH WORK OF STUDENTS OF THE UNIVERSITY IN ENGLISH CLASSES

2020 ◽  
pp. 141-149
Author(s):  
Tat'yana V. Baranova ◽  
Keyword(s):  
English Language ◽  
Research Work ◽  
Scientific Activity ◽  
Educational Process ◽  
State University ◽  
English Classes ◽  
Russian State ◽  
Objective Reasoning ◽  
Oriental Studies ◽  
The University

The present article is dedicated to the problems of the organization and planning of scientific and research work of students of the University in English classes, gives grounds for the purposes and tasks of such competence-forming activity as part of the “Oriental studies” speciality program, the Russian State University for the Humanities. The article analyzes these competences, as well as forms and methods of their formation and development. The author presents demarcation of scientific knowledge and gives its characteristics: using most general qualities of a subject, objective reasoning, argumentativeness, results verifiability and reproducibility, consistency, practicality, capability to change, anticipating the future, making forecasts, methodological reflection. The author tried to analyze the reflexive component of scientific and research work of students in more detail. The article presents possible reflexive positions in the interaction between the teacher and the student and shows the dynamics of this interaction, i.e. gives a hierarchy of positions which the student can occupy in the educational process depending on how independent they are in their activity. The article also highlights the content of scientific and research work of students of the University in English classes on the basis of work with foreign texts in the macro-discourse for the “Oriental studies” speciality. The given foundations of the organization and content of scientific and research work of students have been regularly used in English language classes, as well as in optional forms of scientific activity. The students have shown good results and passion for this kind of work, which confirms the correctness of this approach.

scholarly journals Predictive processes during simultaneous interpreting from German into English

Interpreting ◽  
2017 ◽  
Vol 19 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Ena Hodzik ◽  
John N. Williams
Keyword(s):  
Language Processing ◽  
English Language ◽  
Native Speakers ◽  
Transitional Probability ◽  
Semantic Cues ◽  
Simultaneous Interpreting ◽  
Spoken Language Processing ◽  
Advanced Students ◽  
Native Speakers Of English ◽  
Predictive Processes

We report a study on prediction in shadowing and simultaneous interpreting (SI), both considered as forms of real-time, ‘online’ spoken language processing. The study comprised two experiments, focusing on: (i) shadowing of German head-final sentences by 20 advanced students of German, all native speakers of English; (ii) SI of the same sentences into English head-initial sentences by 22 advanced students of German, again native English speakers, and also by 11 trainee and practising interpreters. Latency times for input and production of the target verbs were measured. Drawing on studies of prediction in English-language reading production, we examined two cues to prediction in both experiments: contextual constraints (semantic cues in the context) and transitional probability (the statistical likelihood of words occurring together in the language concerned). While context affected prediction during both shadowing and SI, transitional probability appeared to favour prediction during shadowing but not during SI. This suggests that the two cues operate on different levels of language processing in SI.

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 .

Measuring second language proficiency with EEG synchronization: how functional cortical networks and hemispheric involvement differ as a function of proficiency level in second language speakers

2009 ◽  
Vol 25 (1) ◽  
pp. 77-106 ◽  
Author(s):  
Susanne Reiterer ◽  
Ernesto Pereda ◽  
Joydeep Bhattacharya
Keyword(s):  
Second Language ◽  
Language Learners ◽  
Language Processing ◽  
English Language ◽  
Second Language Learners ◽  
Right Hemisphere ◽  
Brain Activation ◽  
Frequency Range ◽  
Second Language Processing ◽  
Language Students

This article examines the question of whether university-based high-level foreign language and linguistic training can influence brain activation and whether different L2 proficiency groups have different brain activation in terms of lateralization and hemispheric involvement. The traditional and prevailing theory of hemispheric involvement in bilingual language processing states that bilingual and second language processing is always at least in some form connected to the right hemisphere (RH), when compared to monolingual first language processing, the classical left-hemispheric language-processing domain. A widely held specification of this traditional theory claims that especially bilinguals or second language learners in their initial phases and/or bilinguals with poor fluency and less experience rely more on RH areas when processing their L2. We investigated this neurolinguistic hypothesis with differently proficient Austrian learners of English as a second language. Two groups of L2 speakers (all Austrian German native speakers), differing in their L2 (English) language performance, were recorded on electroencephalography (EEG) during the processing of spoken English language. A short comprehension interview followed each task. The `high proficiency group' consisted of English language students who were about to complete their master's degree for English language and linguistics, while the `low proficiency group' was composed of non-language students who had only school level performance and less training in English. The age of onset of L2 learning was kept constant: 9 years for both groups. To look for cooperative network activity in the brain, EEG coherence and synchronization measures were analysed for a high EEG frequency range (gamma band). Results showed the most significant group differences in synchronization patterns within the lower gamma frequency range, with more RH involvement (extensive right-hemisphere networks) for the low proficiency group, especially when processing their L2. The results can be interpreted in favour of RH theories of second language processing since, once again, we found evidence of more RH involvement in (late) second language learners with less experience and less training in the L2. The study shows that second language training (and resulting proficiency) and/or differences in ability or state of linguistic alertness can be made visible by brain imaging using newly developed EEG-synchronization techniques as a measure.

scholarly journals Proficiency Differences in Syntactic Processing of Monolingual Native Speakers Indexed by Event-related Potentials

2010 ◽  
Vol 22 (12) ◽  
pp. 2728-2744 ◽  
Author(s):  
Eric Pakulak ◽  
Helen J. Neville
Keyword(s):  
Language Proficiency ◽  
Language Processing ◽  
English Language ◽  
Native Speakers ◽  
Memory Span ◽  
Wide Spectrum ◽  
Event Related Potentials ◽  
Related Potentials ◽  
Native Speakers Of English ◽  
Proficiency Scores

Although anecdotally there appear to be differences in the way native speakers use and comprehend their native language, most empirical investigations of language processing study university students and none have studied differences in language proficiency, which may be independent of resource limitations such as working memory span. We examined differences in language proficiency in adult monolingual native speakers of English using an ERP paradigm. ERPs were recorded to insertion phrase structure violations in naturally spoken English sentences. Participants recruited from a wide spectrum of society were given standardized measures of English language proficiency, and two complementary ERP analyses were performed. In between-groups analyses, participants were divided on the basis of standardized proficiency scores into lower proficiency and higher proficiency groups. Compared with lower proficiency participants, higher proficiency participants showed an early anterior negativity that was more focal, both spatially and temporally, and a larger and more widely distributed positivity (P600) to violations. In correlational analyses, we used a wide spectrum of proficiency scores to examine the degree to which individual proficiency scores correlated with individual neural responses to syntactic violations in regions and time windows identified in the between-groups analyses. This approach also used partial correlation analyses to control for possible confounding variables. These analyses provided evidence for the effects of proficiency that converged with the between-groups analyses. These results suggest that adult monolingual native speakers of English who vary in language proficiency differ in the recruitment of syntactic processes that are hypothesized to be at least in part automatic as well as of those thought to be more controlled. These results also suggest that to fully characterize neural organization for language in native speakers it is necessary to include participants of varying proficiency.

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