There were a couple of other features that I wanted to implement within ERA on popular demand. The first step was to include features to modify line and letter spacing which can be useful for some people. Another request was to only highlight important words within sentences. The way I went about this was to use natural language processing to determine important words like nouns, verbs, etc and only bolden these words.
Another key issue was saving documents. Currently I used TextEditor
however this was giving rather strange results and bugs including the entire app crashing or simply issues when saving back to coredata. I ended up using TextField
and specifying the axis: .vertical
specifically to fix this strange bug and it ended up looking a lot cleaner then my TextEdtior
implementation. To save documents I added a specific button and for it to autosave as you exited the document. I had used a previous method to save settings too.
Another issue was not being able to draw upon the image but this was an easy fix as all that was needed was to add another canvas and store another set of data values relating to this canvas.
After conducting market research, users seemed to have difficuly in determining what different symbols. The options were to either make an inital tutorial which seemed rather challenging or to make a short information page with a list of symbols and what they did.
Another highly requested feature was the ability to translate text between languages and this was simpler then I thought. This consited of using google's MLKit to perform on device machine learning and adding a few more UI options.
Gradient reading was developed by simply adding a gradient onto the text but first splitting up the text into appropriate lines. The gradient works by repeatedly changing the colour from black to blue to black to red and back to black. This can help people read faster and more effficiently by maintaining focus.
The app is available here: https://apps.apple.com/gb/app/era-easy-reading-assistant/id6444321235