I mentioned that word processors have in-built spell checkers, but I think we've all experienced the limitations of these in terms of if you're making a mistake with a word where the alternative that you've put in, is that it's still kind of a legal word of English. So for example, if you've confused 'there', t-h-e-r-e, with 'their', t-h-e-i-r, a spellchecker won't necessarily catch that because you have actually potentially spelt the word right. But we do have a new generation of spellcheckers coming through. And some of these are specifically designed for and sometimes by people with dyslexia. So one example is the Ginger spell checker,and again we have a link to this. So what Ginger does, which is clever, is that it actually takes into consideration context o it would actually realize if you are using a word out of context and flag that for you, so this is a really great movement. Ginger, as with many tools, has a kind of free version right now and then also an embellished version that you pay more for. But an intriguing part of the design with Ginger is that as you use it, it's actually collecting data on the errors you're making in the context. So actually, as more and more people use it, it's actually becoming more and more accurate. So again, this is an example of the kind of big data possibilities we have, and how computers can provide a level of sophistication that's really very exciting. Lastly, the opposite of what we talked about in the reading segment in terms of text to speech, there's also speech to text tools. And these are, as we have text to speech, where I've said they've been limited by the power of the technology in providing a good quality voice in that case. But with speech to text there's also been a kind of research and technology limitations that are gradually being broken through by researchers. So speech to text in essence allows you to speak your ideas, and then it's translated immediately into text. Again, the most commonly used versions of this are ones that you pay for, commercial ones. So I think one that's widely known is Dragon Naturally Speaking, that's one example. These kind of things are, I would use them with caution with younger children because they actually, they're not without their frustrations and I think some people like to use them, some people find them quite tricky. The trick is at the beginning you train the software to recognize your particular voice. There's the calibration stage where you're shown sentences to read and so obviously the computer knows what it's expecting and learns to recognize your specific way of speaking these. So, that can actually be quite frustrating for younger learners and especially when it will make some mistakes. And so you have to sometimes go back and say things again. So I think you need a level of patience and strategy to be able to use these effectively. It could also be an issue for children who maybe English is not their first language and they have a fairly strong accent. At the moment these softwares, they're best tailored for the accents of the country within which they're available. So for example, when I was living in America a few years ago the American software had a great deal of difficulty understanding, or even calibrating to my accent, it just wasn't in the algorithms. So that's something that you do need to be aware of. So be tentative if a child has an accent, because you want to avoid the kind of frustrating experience for them. So one other thing that is important to remember with a voice detect software is that although you might think well, this is going to really solve a lot of problems. If I have an essay to do and I can just talk into this machine and it will produce my essay. But it's important to think that actually, even when we're trying to enunciate clearly and reduce the number of hesitations, as I'm doing right now. I'm trying to reduce my number of 'uhs', which has varied success. But you'll notice that it's actually quite hard to speak in exactly the same way that we would write. There is more hesitation, you might be circumlocuting, so kind of rambling around a bit. You're going to use turns of phrase that you might not use in writing. So actually, it can be quite a cognitively demanding task to think and then to speak and not then have to kind of go back and get rid of all your 'ers' and your hesitations and your 'ums' and the misheard words. So for some people, this is actually add cognitive demands rather than take them away. So before you spend lots of money on this kind of thing really try it out. See if it's going to work for the individual. You need some patience. You do need the strong language skills to be able to do this. And I think you need the motivation to go through the calibration stages and also to be willing to do the backtracking. And help the software when it's got something wrong, so these things can definitely be very powerful. And again the technology to be able to deal with different accents and indistinct sounds is moving at exponential rates. So things will just get better and better, and more and more possible in this area. Especially as now voice-activated systems have a very wide applicability across the population in terms of people's phones using voice commands. People turning their lights on at home with voice command, so this kind of technology is a high priority for advance. But, yes, I think just be cautious and see if it works in the individual case. So that's a roundup of writing technology, again it's a few ideas, there's lots out there. And actually even general websites like a lifehacker.com is one example, this is a website that just tries to give kind of shortcuts for different life activities. You can often find some quite good ideas on these for shortcuts for reading, for writing, for organization. So keep your eyes out, experiment with things, and hopefully this will help make the process that slightly bit smoother.
