Correction of Noisy Natural Language Text is an important and well studied problem in Natural Language Processing. It has a number of applications in domains like Statistical Machine Translation, Second Language Learning and Natural Language Generation. In this work, we consider some statistical techniques for Text Correction. We define the classes of errors commonly found in text and describe ...

Malapropism is a type of semantic errors. It replaces one content word by another content word similar in sound but semantically incompatible with the context and thus destructing text cohesion. We propose to signal a malapropism when a pair of syntactically linked content words in a text exhibits the value of a specially defined Semantic Compatibility Index (SCI) lower than a predetermined thr...

In the article by Okada et al, “Sympathetic Neural and Hemodynamic Responses During Cold Pressor Test in Elderly Blacks and Whites,” which published online on March 28, 2016, and appeared in the May 2016 issue of the journal (Hypertension. 2016;67:951–958. DOI: 10.1161/ HYPERTENSIONAHA.115.06700), a correction is needed. Figures 2 and 3 that had missing text due to a publication error have been...

Contextual spell correction is very important for real word error correction. It gives the correct word for an incorrect word in a particular sentence. The traditional spell checker can correct those misspelled words which are not present in dictionary but here we try to develop a spell checker which can give appropriate word on the basis of the contextual meaning of the sentence. This spell ch...

We analyze the performance of encoder-decoder neural models and compare them with wellknown established methods. The latter represent different classes of traditional approaches that are applied to the monotone sequence-to-sequence tasks OCR post-correction, spelling correction, grapheme-to-phoneme conversion, and lemmatization. Such tasks are of practical relevance for various higher-level res...

Portuguese is a less resourced language in what concerns foreign language learning. Aiming to inform a module of a system designed to support scientific written production of Spanish native speakers learning Portuguese, we developed an approach to automatically generate a lexicon of wrong words, reproducing language transfer errors made by such foreign learners. Each item of the artificially ge...

This paper describes our ongoing research project on text simplification for congenitally deaf people. Text simplification we are aiming at is the task of offering a deaf reader a syntactic and lexical paraphrase of a given text for assisting her/him to understand what it means. In this paper, we discuss the issues we should address to realize text simplification and report on the present resul...

In this work, we investigate the use of error-correcting output codes (ECOC) for boosting centroid text classifier. The implementation framework is to decompose one multi-class problem into multiple binary problems and then learn the individual binary classification problems by centroid classifier. However, this kind of decomposition incurs considerable bias for centroid classifier, which resul...

Instructional grammar is often used in Computer-assisted Language Learning (CALL) and the grammatical error detection is an important feature. However, it is not an easy task in Chinese language. There is no delimiter separating consecutive words in Chinese sentences. Word segmentation is a process in which proper word boundaries are identified. Before syntactic parsing of a Chinese sentence, w...

We present here a general-purpose spell and grammar error detection architecture for Catalan unrestricted text. This architecture is based on a previous existing shallow morphosyntactic parser, which had to be adapted in order to successfully handle ill-formed input. The goal of this research is to obtain an architecture that can be used for developing morphosyntactic error checkers for both na...