You can configure Word so that it doesn’t report URLs and other special items as misspellings. But if you have a long list of words to add, it’s best to do so by editing the dictionary file itself. When you’re done, click OK to exit the dictionary.Īdding words one at a time is sensible if you have only a few. Click the custom.dic file–or the name of the dictionary to add the words to, if you are using a special dictionary–and click Edit Word List. If you know ahead of time that you will be using some unusual words, and if you do not want Word to report them as possible misspellings, you can add them to the dictionary.Ĭhoose File, Options, Proofing, and click Custom Dictionaries. If you use an obscure word often, you can get Word to stop flagging it. Here you should click the language to use for the selected text the listed languages displaying checkmark icons are available for use in checking spelling. ![]() ![]() Then click Language and choose Set Language in the Proofing group of buttons. To arrange this, select the text in French (or whatever foreign language you’re using), and click the Review tab on the Ribbon toolbar. If you don't need suggestions from your results you don't need to add the spelling extractor, TextRazor is already correcting obviously misspelled entities for all your requests.You can avoid that situation by setting Word to check the French text using a French word list. There is no additional charge for enabling this analysis on your documents. Simply add the spelling extractor to your request, and look for the 'spellingSuggestions' field with each word in the response. The TextRazor spelling correction system is fully integrated with the TextRazor analysis pipeline. On the results page under 'sentences' you can see the suggestions column populated next to each word. You can try out the Spelling Correction system with your own documents through our Online Demo. We plan to extend support to other languages with demand, if you are interested in spelling correction for another language please let us know. Spelling Correction is currently only available in English. TextRazor's language models are updated frequently, so we're constantly learning new words as language evolves. Trained using billions of words, TextRazor knows about slang, people's name variations, and brand names. TextRazor uses state-of-the-art Recurrent Neural Network language modelling to help understand whole sentences, so it is able to correct words in context and generate suggestion scores based on the grammatical 'correctness' of each word in the sentence. ![]() Correct and score thousands of words per second. ![]() Generate a confidence score for each correction suggestion using a deep analysis of the sentence context.Identify incorrect homophones - words with the same pronunciation but different meanings ( mail vs male).Detect typos in millions of real world entities like people, places and brands that aren't necessarily in the dictionary.TextRazor's solution offers significant advantages: Traditional spellcheckers rely on dictionaries and hardcoded rules. TextRazor's Deep Spelling Corrector takes technology a step beyond the spellcheckers that you might find in a word processor. Our state-of-the-art spelling correction algorithms check your content for spelling errors and generate ranked contextual corrections, with results easily integrated into your app through a simple API call. Typos in names and keywords can cause huge problems for text analysis systems, especially when working with noisy Tweets or social data.
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