This is not as significant as it may seem since the number of transposition errors are not as common as other errors in Bangla. One notable limitation is the inability to handle transposition errors as a single edit distance errors.

In terms of error detection and correction, the algorithm uses the statistics of Bangla error pattern and thus produces a small number of significant suggestions. The use of finite state representation for the word implies hat the algorithm is much more efficient in the case of non- inflected forms in case of nouns, it is even more significant as Bangla nouns are heavily used in the non-inflected form. We start by using a finite state representation for all the words in the Bangla dictionary the algorithm then uses the state tables to test a string, and in case of an erroneous string, try find all possible solutions by attempting singular and multi-step transitions to consume one or more characters and using the subsequent characters as look-ahead and finally, we use backtracking to add each possible solution to the suggestion list. FSA has proven to be an effective method for problems requiring probabilistic solution and high error tolerance. We propose an alternative approach to checking the spelling of Bangla text that uses a finite state automaton (FSA) to probabilistically create the suggestion list for a misspelled word. Spelling checker algorithms using edit- distance methods tend to produce a large number of possibilities for misspelled words. Precisely, the test results demonstrated the awareness of advantage and disadvantages of the measurement which were adapted and applied to a search for meaning by using Jaccard similarity coefficient.Ī crucial figure of merit for a spelling checker is not just whether it can detect misspelled words, but also in how it ranks the suggestions for the word. Furthermore, the performance of this proposed similarity measurement method was accomplished by employing precision, recall, and F-measure. Technically, we developed a measure of similarity Jaccard with Prolog programming language to compare similarity between sets of data. Thus, this paper proposed the similarity measurement method between words by deploying Jaccard Coefficient. Consequently, a similarity measurement between keywords and index terms is essentially performed to facilitate searchers in accessing the required results promptly. Particularly, information retrieval results as documents are typically too extensive, which affect on accessibility of the required results for searchers. Additionally, an index of search engines has to be updated on most recent information as it is constantly changed over time. This allows users to specify the search criteria as well as specific keywords to obtain the required results. Presently, information retrieval can be accomplished simply and rapidly with the use of search engines. The datasets and codes used in this work are freely available at combination of bigram and trigram, and generates suggestions based on the Cosine similarity measure with the accuracy rate of 94.29% individually. The grammar checker detects errors based on language model probability i.e. The spell checker uses the Double Metaphone algorithm and Edit distance based on the distributed lexicons and numerical suffix dataset to detect all types of Bangla spelling mistakes with an accuracy rate of 97.21% individually. Based on these corpus and lexicon, we have developed a combined spell and grammar checker application that simultaneously detects distinct spelling and grammatical mistakes and provides appropriate suggestions for both as well. At first, a full-fledged and generalised Bangla monolingual corpus comprising over 100 million words has been built by scraping reputed, diversified online sources and then an extensive Bangla lexicon consisting of over 1 million unique words has been extracted from that corpus. Considering the lack of research efforts, we demonstrate the development of a comprehensive Bangla spell and grammar checker with necessary resources. A spell and grammar checker is profoundly essential for diverse publications especially for Bangla language in particular as it is spoken by millions of native speakers around the world.

Norvig spelling corrector