Natural Language Processing with Improved Deep Learning Neural Networks

As one of the core tasks in the field of natural language processing, syntactic analysis has always been a hot topic for researchers, including tasks such as Questions and Answer (Q&A), Search String Comprehension, Semantic Analysis, and Knowledge Base Construction. This paper aims to study the application of deep learning and neural network in natural language syntax analysis, which has significant research and application value. This paper first studies a transfer-based dependent syntax analyzer using a feed-forward neural network as a classifier. By analyzing the model, we have made meticulous parameters of the model to improve its performance. This paper proposes a dependent syntactic analysis model based on a long-term memory neural network. This model is based on the feed-forward neural network model described above and will be used as a feature extractor. After the feature extractor is pretrained, we use a long short-term memory neural network as a classifier of the transfer action, and the characteristics extracted by the syntactic analyzer as its input to train a recursive neural network classifier optimized by sentences. The classifier can not only classify the current pattern feature but also multirich information such as analysis of state history. Therefore, the model is modeled in the analysis process of the entire sentence in syntactic analysis, replacing the method of modeling independent analysis. The experimental results show that the model has achieved greater performance improvement than baseline methods.

Recognition of spatial data from natural language texts for the purpose of visualization

This paper describes one of the possible implementation options for the recognition of spatial data from natural language texts. The proposed option is based on the lexico-syntactic analysis of texts, which requires the use of special grammars and dictionaries. Spatial data recognition is carried out for their subsequent geocoding and visualization. The practical implementation of spatial data recognition is done using a free, freely distributed software tool. Also, some applications of spatial data are considered in the work and preliminary results of spatial data recognition are given.

Tłumaczenie symultaniczne mowy noblowskiej w dydaktyce przekładu konferencyjnego

Simultaneous Interpreting of a Nobel Lecture in Conference Interpreter Training Simultaneous interpreting with text is a hybrid mode combining simultaneous with sight translation. As it constitutes an important element of the interpreter’s work, it must then be a component of conference interpreter training. Due to a scarce research in the field so far, the aim of this paper is to discuss an empirical longitudinal study of simultaneous interpreting of a Nobel lecture from Spanish into Polish. The results of the analysis show that during the preparation phase, it is not a selective analysis of such lexical items as proper names, numbers or unknown words, but rather a syntactic analysis, which enables to render compound statements in a specific register, as well as an in-depth cultural analysis, which contributes to acquiring knowledge across different fields necessary in conference interpreting.

A unified deep neuro-fuzzy approach for COVID-19 twitter sentiment classification

Covid-19 braces serious mental health crisis across the world. Since a vast majority of the population exploit social media platforms such as twitter to exchange information, rapid collecting anf analyzing social media data to understand personal well-being and subsequently adopting adequate measures could avoid severe socio-economic damage. Sentiment analysis on twitter data is very useful to understand and identify the mental health issues. In this research, we proposed a unified deep neuro-fuzzy approach for Covid-19 twitter sentiment classification. Fuzzy logic has been a very powerful tool for twitter data analysis where approximate semantic and syntactic analysis is more relevant because correcting spelling and grammar in tweets are merely obnoxious. We conducted the experiment on three challenging COVID-19 twitter sentiment datasets. Experimental results demonstrate that fuzzy Sugeno integral based ensembled classifers succeed over individual base classifiers.

Self help books and their titles – a lexical and syntactical analysis

The article presents results of an analysis of titles of English self-help books as animportant phenomenon of pop culture. The focus was placed on the role of the title bothas a key factor for the consumer decision-making process and as a carrier of culturalthought or an element of culture. Individual titles of self-help publications were dividedaccording to, among others, their length, structural and semantic features. The lexicallayer was discussed with particular emphasis on the elements that stand out from theselected research material. A syntactic analysis was undertaken in order to identify themost common structures to determine whether there is a rule for titling self-help booksthat would ensure their commercial success. The article also mentions the problemof intertextual references and rhetorical procedures that make titles more attractiveand perform advertising functions. The subject under scrutiny spans several branchesof science, including psychology and sociology.

Osservazioni sull’uso di yád in antico indiano

This paper considers the placement of the complementizer yád within the sentence and the functional value of yád in Old Indian. It will be noted that thecomplementizer yád, like other subordinating conjunctions in some ancient and modern Indo-European languages, can be preceded by a topicalized or a focalized phrase in its clause. In particular, in R̥gVeda there are many cases where yád is preceded by an element which seems to have moved from inside the sentence and also cases where yád is preceded by the inflected verb. Morover, some cases will be discussed showing the use of yád to introduce clauses governed by verbs of saying and knowing, both in Vedic and in Sanskrit, and a possible syntactic analysis of these structures.

From Graphematics to Phrasal, Sentential, and Textual Semantics Through Morphosyntax by Means of Corpus-Driven Grammar and Ontology: A Case Study on One Tibetan Text

This article presents the current results of an ongoing study of the possibilities of fine-tuning automatic morphosyntactic and semantic annotation by means of improving the underlying formal grammar and ontology on the example of one Tibetan text. The ultimate purpose of work at this stage was to improve linguistic software developed for natural-language processing and understanding in order to achieve complete annotation of a specific text and such state of the formal model, in which all linguistic phenomena observed in the text would be explained. This purpose includes the following tasks: analysis of error cases in annotation of the text from the corpus; eliminating these errors in automatic annotation; development of formal grammar and updating of dictionaries. Along with the morpho-syntactic analysis, the current approach involves simultaneous semantic analysis as well. The article describes semantic annotation of the corpus, required by grammar revision and development, which was made with the use of computer ontology. The work is carried out with one of the corpus texts – a grammatical poetic treatise Sum-cu-pa (VII c.).

Serial verbs in modern standard Arabic

This paper aims to discuss serial verb constructions in Modern Standard Arabic (MSA). It argues against the claim that this structure does not exist in MSA. We examined parallel structures in this paper: being verbs and what is called albadal ‘apposition’ in the traditional grammar of the Arabic language. This paper argues that the first structure should be analyzed as an auxiliary structure that contains two clauses, while the second structure should be analyzed as a serial verb structure as it denotes, among others, a complex situation, shares the same subject, and contains one clause. Finally, this paper provides a brief syntactic analysis for being verbs and serial verbs in MSA within the lexical functional grammar (LFG) framework, showing the differences between the two structures.