Furthermore, previous research has demonstrated that writing patterns on social media differ from business or academic writing . Although photos and videos are common, written text is still a key form of communication on social media. One example is social media, which is thoroughly integrated into daily life, with more than 79% of Americans using Facebook and 24% using Twitter.
#Phil cook nmt facebook professional
While most research on dyslexia investigates academic or professional settings, many everyday activities rely on reading and writing. Participants reacted positively to the tool and reported increased confidence in writing after using it. AWH provides suggestions for common dyslexia style spelling mistakes (not content), but currently does not learn and accommodate individual unique patterns of spelling errors and writing style. We also deployed our model to power an “Additional Writing Help” (AWH) tool (Figure 1) for writing comments on Facebook and conducted a field study with 19 participants with dyslexia. We evaluated our model with datasets of dyslexia style text from social media and other sources, and performance was often comparable to mass market tools.
Second, using the technique of back-translations (and data augmentation in general ), we were able to generate a large scale synthetic training data by utilizing public text available on SNSs and injecting common dyslexia writing issues into the text to train our model. First, we applied a sequence-to-sequence (seq2seq) model with a character encoder. This is a novel approach for both Neural Machine Translation (NMT) and dyslexia spell checking , and we have made two major technical contributions. The idea is to “translate” text with common dyslexia writing issues to text without, while preserving slang, abbreviations, and hash/mention tags.
To address this, we designed and trained a Neural Machine Translation (NMT) based spell/grammar checking model to be sensitive to dyslexia specific errors and accustomed to the social media context. Second, most existing tools were designed for formal writing tasks such as homework assignments and work communications, making it difficult to provide suggestions or corrections for social media's linguistic and communication style. First, designed for the general population, these tools are generally less reliable at identifying and remedying the errors that people with dyslexia are prone to making. Although existing general writing tools, such as spell checkers and auto-correct, provide value to the dyslexia community , there are some major issues with current tools. To better support this community, we designed and evaluated a dyslexia-specific writing support tool to increase confidence and reduce anxiety associated with writing on social media. Thus, dyslexia can present an obstacle to one's self representation on social media.
Previous research showed that people with dyslexia face challenges when writing on social media and that writing creates a tension between the freedom of self-expression and the social stigma around “bad” writing. Although the effect of dyslexia varies widely, it often impacts the ability to process and recognize text.
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