Simply say "Hey Google, open Assistant settings", and choose voice as your preferred input choice. Voice control is available on iPad and iPhone on iOS 13 or later. This video will help with using it on Big Sur, the latest iOS and shows how to use dictation and also to use voice control. There haven't been too many changes since Catalina. Different languages can also be added once files have been downloaded. Intelligent personal assistants are an important feature of all modern tablets and smartphones.
They use voice recognition technology and a natural language user interface to provide a range of services. Some of the most popular personal assistants include:. These personal assistants offer similar features to help with everyday tasks — responding to voice commands and requests to provide information and answer queries through online sources , sending messages and emails, making phone calls, taking notes, scheduling meetings, and playing music. Voice recognition programmes work by analysing sounds and converting these to text.
The software draws on a vast vocabulary and a knowledge of how English is spoken to determine what the speaker most probably said. In some programmes, specialist vocabulary or frequently used words such as names can be added through giving it documents, word lists, or using 3 rd party plugins.
Voice recognition software captures and converts speech via a microphone. Some computers include built-in microphones, but most specialist voice recognition programmes also include a microphone headset.
This can be connected to the computer, either through its soundcard socket or via a USB or similar connection. It is also possible to use a suitable hand-held digital recorder to dictate recordings — something that may be especially useful for mobile working.
Some voice recognition applications can transcribe recordings from a number of formats including wav, mp3 and wma. This only takes a minute and simply involves reading a short text of a few lines. However, not all most recognition software uses enrolment but may require the user to say if they have an accent and to choose which one. When talking, people often hesitate, mumble or slur their words. One of the key skills in using voice recognition software is learning how to talk clearly so that the computer or device can recognise what is being said.
It can help to plan what to say and then to speak in complete phrases or sentences. Voice recognition software can misunderstand some of the words you speak and may put in similar-sounding words, so it can be important to proofread carefully.
While voice recognition software is improving all the time, the error rate can still be quite high. If corrections are made using voice recognition software either by voice or by typing, it can adapt and learn so that, hopefully, the same mistake will not occur again.
It can be possible to achieve very high levels of accuracy with careful dictation and correction, and perseverance. The text-to-speech facility is especially useful for people with a sight impairment who would find it difficult or impossible to read any text file and for anyone with dyslexia.
Training is really useful for users to realise the full benefits of working with voice recognition programmes. To get the best from training, it can be helpful to spread it out over a period of weeks — giving the user sufficient opportunity to practice new skills and consolidate their learning between formal coaching sessions. Training will be most effective when it is geared towards the specific needs of the individual, focusing on their particular tasks and challenges.
Specialist vocabularies can be attained by using plugins or by giving the programme access to emails and documents.
A wide range of private and voluntary organisations offer computer training services. The AbilityNet factsheet on Technical help and training resources gives contact details for many organisations that provide ICT training and support for disabled people.
Apple provides tutorials and guidance on setting dictation on the Mac. Windows provides tutorials for their voice recognition. Nuance provides extensive tutorials and support for their Dragon products. These programmes are all moderately priced, with a free version of NaturalReader also being available.
My Computer My Way is an AbilityNet run website packed with articles explaining how to use the accessibility features built into your computer, tablet or smartphone.
The site is broken down into the following sections:. Use it for free at mcmw. Many of our volunteers are former IT professionals who give their time to help older people and people with disabilities to use technology to achieve their goals. Our friendly volunteers can help with most major computer systems, laptops, tablet devices and smartphones. View a copy of this license at creativecommons. My Computer My Way Vision - seeing the screen Hearing - hearing sound Motor - using a keyboard and mouse Cognitive - reading and spelling.
Print this page. This factsheet provides an overview of how you can use voice recognition. You can use voice recognition to control a smart home, instruct a smart speaker, and command phones and tablets. In addition, you can set reminders and interact hands-free with personal technologies. The most significant use is for the entry of text without using an on-screen or physical keyboard. Communication technology continues to evolve rapidly.
Using voice recognition to input text, check how words are spelt and dictate messages has become very easy. Most on-screen keyboards have a microphone icon that allows users to switch from typing to voice recognition easily.
When sound waves are fed into the computer, they need to be sampled first. Sampling refers to breaking down of the continuous voice signals into discrete, smaller samples- as small as a thousandth of a second. These smaller samples can be fed directly to a Recurrent Neural Network RNN which forms the engine of a speech recognition model.
But to get better and accurate results, pre-processing of sampled signals is done. Pre-processing is important as it decides the efficiency and performance of the speech recognition model. They are then pre-processed, which is breaking them into a group of data. Generally grouping of the sound wave is done within interval of time mostly for milliseconds. This whole process helps us convert sound waves into numbers bits that can be easily identified by a computer system. Inspired by the functioning of human brain, scientists developed a bunch of algorithms that are capable of taking a huge set of data, and processing that it by drawing out patterns from it to give output.
These are called Neural networks as they try to replicate how the neurons in a human brain operate. They learn by example. Neural Networks have proved to be extremely efficient by applying deep learning to recognize patterns in images, texts and speech. Recurrent Neural networks RNN are the ones with memory that is capable of influencing the future outcomes. So RNN reads each letter with the likelihood of predicting the next letter as well. RNN saves the previous predictions in its memory to accurately make the future predictions of the spoken words.
Using RNN over traditional neural networks in preferred because the traditional neural networks work by assuming that there is no dependence of input on the output. They do no use the memory of words used before to predict the upcoming word or portion of that word in a spoken sentence. So RNN not only enhances the efficiency of speech recognition model but also gives better results. It is the hidden memory. It stores the data of what things took place in all the previous or past time steps.
It is calculated as:. It implies that by passing various inputs at different steps, the same task is being done at every step. This limits the number of parameters to be learned. Even though there is an output at each time step, dependence on the task to perform is not required.
To make it easier to understand, consider an example where we have to predict the output of a sentence. To do so, we won't concern ourselves with the output of each word, but with the final output. Same implies for the inputs as well, that is, we do not need input at each time step. So far, we know that in RNN, the output at a certain time step not only depends on the current time step but also on the gradients calculated in the past steps. In order to do so, you will have to back propagate 5 steps and sum up all the gradients.
This method of training an RNN has one major drawback. This makes the network to depend on steps which are quite apart from each other. We know that RNN cannot process very long sequences. They consist of cell state that allow any information to flow through it.
By applying gates, any information can also be added or removed. LSTM employ three types of gates: input gate, output gate and forget gate. However, looking through all its features and functionalities, we can see that even persons without disabilities could enjoy and maximize the use of this feature.
This is most useful to people who are totally blind and struggle to use a touch-screen keyboard. Also, people with limited motor-functions will hugely benefit from this feature. Persons with temporary and situational disabilities will benefit as well. Even those sighted people whose hands are busy and want to use their phone or tablet will experience the ease that this feature brings. The thing that immediately caught my attention is the simplicity of setting up Voice Control.
At first, I thought I would need to set up my voice for recognition purposes, but it is no longer necessary. I activated Voice Control in both my phones: in my iPhone 8 and in my iPhone 6s.
The most glaring difference that I immediately noticed is the responsiveness of Voice Control and the iPhone in general. As expected, my iPhone 8 is faster to respond.
The delays are very minimal. My iPhone 6s is still working fine, though. It can still keep up with Voice Control. Another thing I noticed in both my phones is that when Voice Control is active, the batteries drain a little too fast and the temperature of the phone increases. These experiences instantly made me ponder — is it practical to sacrifice my battery life over the convenience I can get from using voice commands?
But as I started to explore deeper, I realized how helpful it truly is for a user like me. Navigation-wise, Voice Control is very efficient, and the response is consistent. This is commonly my struggle with Siri. When these are turned on, the confirmations and hints can sometimes cause distraction.
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