Rule-Based Grammar and spell checking is the task of content any specific language using a particular set rules for their grammar spellings checking. In this work, libraries functions Python useful Natural Language Processing are used to perform Spell Libraries NLTK (for Sentence Boundary Detection POS tagging), pyEnchant by comparing with standard dictionary), Inflect indefinite article). The ...

In computing, spell checking is the process of detecting and sometimes providing spelling suggestions for incorrectly spelled words in a text. Basically, a spell checker is a computer program that uses a dictionary of words to perform spell checking. The bigger the dictionary is, the higher is the error detection rate. The fact that spell checkers are based on regular dictionaries, they suffer ...

Abstract The Standard Precipitation Index (SPI) is a widely used statistical technique for the characterization of droughts. It based on probabilistic standardization procedure, which converts Gamma-type probability distribution function (PDF) into normal (Gaussian) standard series with zero mean and unit deviation. Drought classification SPI indicates dry wet spell characteristics, provided th...

With the support of the DGLFLF, ELDA conducted an inventory of existing language resources for the regional languages of France. The main aim of this inventory was to assess the exploitability of the identified resources within technologies. A total of 2,299 Language Resources were identified. As a second step, a deeper analysis of a set of three language groups (Breton, Occitan, overseas langu...

Contextual spelling errors are defined as the use of an incorrect, though valid, word in a particular sentence or context. Traditional spelling checkers flag misspelled words, but they do not typically a t tempt to identify words that are used incorrectly in a sentence. We explore the use of Latent Semantic Analysis for correcting these incorrectly used words and the results are compared to ear...

Real-word spelling correction differs from non-word spelling correction in its aims and its challenges. Here we show that the central problem in real-word spelling correction is detection. Methods from non-word spelling correction, which focus instead on selection among candidate corrections, do not address detection adequately, because detection is either assumed in advance or heavily constrai...