Text Processing

This paper reports on the application of the Text Attribution Tool (TAT) to profiling the authors of Arabic emails. The TAT system has been developed for the purpose of language-independent author profiling and has now been trained on two email corpora, English and Arabic. We describe the overall TAT system and the Machine Learning experiments resulting in classifiers for the different author traits. Predictions for demographic and psychometric author traits show improvements over the baseline for some of the ...

This paper analyzes free online programs for sentiment analysis which can, on the bases of their algorithm, give a positive, negative or neutral opinion of a text. At the beginning of the paper sentiment analysis programs and techniques they use such as Naive Bayes and Recurrent Neural Networks are presented. The programs are divided into two categories for analysis. The first category consists of sentiment analysis programs which analyze texts written or copied inside the user interface. The second category consists of programs for analyzing opinions posted on social networks, blogs, and other media sites. Programs from both categories were chosen for this research on the bases of positive reviews on computer science portals and their popularity on web search engines such as Google and Bing. The accuracy of the programs from the first category was checked by inserting the same sentence from movie review and comparing the results. Their additional options have also been analyzed. For the second category of programs, it was determined which social networks, blogs, and other social media they cover on the internet. The purpose of this analysis was to check the overall quality and options that free sentiment analysis programs provide. An example of how to create one's own custom sentiment analyzer by using the available Python code and libraries found online is also given. Two simple programs were created using Python. The first program belongs to the first category of programs for analyzing an input text. This program serves as a pilot program for Croatian which gives only the basic analysis of sentences. The second program collects recent tweets from Twitter containing certain words and creates a pie chart based on the analysis of the results.

India is a country of having multi spoken languages and there is a need in digitization of books and documents and conversion of this text of these books and documents into speech. This paper envisages on design and implementation of Text to Speech system for English and Konkani language using image recognition technology (Optical Character Recognition) and to develop a cost effective text image to speech conversion system using MATLAB. The main aim of this project is to recognize the text character of an image and convert this text into speech signal. To achieve this, text contained in the page is first pre-processed. The pre-processed unit prepares this text for recognition. Then this text is segmented to separate out the characters from each other. After Segmentation, letters are extracted and resized and stored them in the text file. This process is done with the help of MATLAB. This text is then converted into speech. This paper also uses Devanagri script.

The paper reports work on collecting and annotating code-mixed English-Hindi social media text (Twitter and Facebook messages), and experiments on automatic tagging of these corpora, using both a coarse-grained and a fine-grained part-ofspeech tag set. We compare the performance of a combination of language specific taggers to that of applying four machine learning algorithms to the task (Conditional Random Fields, Sequential Minimal Optimization, Naive Bayes and Random Forests), using a range of different features based on word context and wordinternal information.

The processing of reggaeton songs demands an active engagement from the listener due to high level of fragmentation in the lyrics, which stems from variability in word stress and prosodic segmentation. Changes in word stress challenge the listener’s ability to parse the lyrics, and often render the passage semantically and grammatically opaque. Long, deliberate pauses and rhythmic variations within grammatical units can be a hindrance to the perception of certain passages, and hence, to overall comprehension of the text. However, the prosodic disjointedness is compensated by semantic and grammatical links between the parts of separated structures.

N-grams have been widely investigated for a number of text processing and retrieval applications. This article examines the performance of the digram and trigram term conflation techniques in the context of Arabic free text retrieval. It reports the results of using the N-gram approach for a corpus of thousands of distinct textual words drawn from a number of sources representing various disciplines. The results indicate that the digram method offers a better performance than trigram with respect to conflation precision and ...

We present the first comprehensive review of research into hemianopic dyslexia since Mauthner's original description of 1881. We offer an explanation of the reading impairment in patients with unilateral homonymous visual field disorders and clarify its functional and anatomical bases. The major focus of our review is on visual information processing, visuospatial attention and eye-movement control during reading. An advanced understanding of the basis of hemianopic dyslexia and its rehabilitation also increases our knowledge about normal reading and its underlying neural mechanisms. By drawing together various sources of evidence we illustrate the significance of bottom-up and attentional top-down control of visual information processing and saccadic eye-movements in reading. Reading depends critically on the cortical–subcortical network subserving the integration of visual, attentional and oculomotor processes involved in text processing.

8
th International Conference on Signal Processing and Pattern Recognition (SIPR 2022) is a
forum for presenting new advances and research results in the fields of Digital Processing and
Pattern Recognition. The conference will bring together leading researchers, engineers and
scientists in the domain of interest from around the world.
Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences.

This paper describes an own implementation of a regular expression preprocessor written in PHP. It extends the regular expression functionality by allowing users to define named segments. These segments include custom character classes, matching groups etc. The pre-processor allows for writing complex regular expressions that are simpler to maintain. In addition, this paper presents a use case of the practical utilisation of the pre-processor. Furthermore, it includes a comparison of expressions written with and without user-defined segments.

How different cultures react and respond given a crisis is predominant in a society's norms and political will to combat the situation. Often, the decisions made are necessitated by events, social pressure, or the need of the hour, which may not represent the nation's will. While some are pleased with it, others might show resentment. Coronavirus (COVID-19) brought a mix of similar emotions from the nations towards the decisions taken by their respective governments. Social media was bombarded with posts containing both positive and negative sentiments on the COVID-19, pandemic, lockdown, and hashtags past couple of months. Despite geographically close, many neighboring countries reacted differently to one another. For instance, Denmark and Sweden, which share many similarities, stood poles apart on the decision taken by their respective governments. Yet, their nation's support was mostly unanimous, unlike the South Asian neighboring countries where people showed a lot o...

[Table of Contents]
http://www.cup.es/us/catalogue/catalogue.asp?isbn=9780521833356&ss=toc
Chapt. 38.  Inferences during discourse comprehension in Korean (pp. 474-483)
- Soyoung Kim Suh, Jung-Mo Lee and Jae-Ho Lee -

Publishers: Cambridge University Press
(pp. 638) (ISBN: 978-0-521-83335-6)

This paper reports on the application of the Text Attribution Tool (TAT) to profiling the authors of Arabic emails. The TAT system has been developed for the purpose of language-independent author profiling and has now been trained on two email corpora, English and Arabic. We describe the overall TAT system and the Machine Learning experiments resulting in classifiers for the different author traits. Predictions for demographic and psychometric author traits show improvements over the baseline for some of the ...

One of our studies is upon the comparison of the nature of Moore's and Hopcroft's algorithms. This gives some new insight in both algorithms. As we shall see, these algorithms are quite different both in behavior and in complexity. In particular, we show that it is not possible to simulate the computations of one of the algorithm by the other. We describe the minimization algorithm by fusion for so-called local automata. A special case of minimization is the construction o minimal automata for finite sets. We consider briefly this case, and in particular describe incremental algorithms. Finally, we consider the case of updating a minimal automaton when a word is added or removed from the set it recognizes.