Speech recognition with artificial intelligence

Even though we are still some way away from this kind of artificial intelligence in speech recognition: who doesn't know the droids from the Star Wars films? Likeable and almost human, the tin men played their way into our hearts. R2-D2’s constant companion, C-3PO, with his golden armour, could already speak, understand and act independently.

Nevertheless, the world of speech recognition technology is in a state of upheaval. Humans still have the upper hand; a computer cannot understand the meaning of spoken word per se, but technology is catching up. Thanks to artificial intelligence, what is already working wonderfully today is the automatic conversion of spoken words into written text.

Speech recognition technology has developed rapidly in recent years. What does not faze the human ear is much more difficult for machines. On the one hand, they have to separate relevant and irrelevant audio information – background noises and hissing, for example – and secondly, they have to interpret this information correctly. By applying ‘artificial intelligence’ in the form of so-called ‘neural networks’, it becomes possible to quickly recognise and correctly interpret the huge amounts of data needed to achieve accurate results in speech recognition.

For user groups such as doctors or lawyers, corresponding special vocabulary can be stored too. This saves the user from having to learn the software and ensures optimum recognition quality right from the beginning.

‘Neural networks’ are a type of deep learning, i.e., a machine learning algorithm. Neural networks allow computers to learn without following explicit programming instructions. This is done by using a mathematical process to mimic how our brains learn. Neural networks consist of specialised, mathematically computable ‘neurons’ that map between input data and output data. This process is called pattern recognition. In other words, computers can use neural networks to recognise patterns in streams of input data (e.g. speech) and then generate an output (e.g. text).

These networks are ‘trained’ with large data sets, which means that the more data they analyse, the more accurate their prediction will be.

Processing the speech information and transforming it into text requires correspondingly large computer resources. The basic prerequisite for good recognition is the right IT infrastructure. Speech recognition from the cloud is a good alternative that does not overload a user’s computer, therefore. Until nowadays, this was not possible with professional speech recognition solutions. Only now, products that close this gap are emerging onto the market. The software is very easy to use, especially for users, and produces the best results. Unusual proper names or unknown words, however, must be corrected afterwards. But thanks to artificial intelligence, speech recognition learns and gets better every time.

The rapid creation of documents has never been easier. The combination of digital recordings and speech recognition makes it possible to use one’s own labour much more efficiently and increase productivity. The item with the greatest potential for optimisation and time savings is writing itself, and great results guarantee high levels of user acceptance. Deciding to use a speech recognition solution pays off with time savings of at least 50 percent when typing. Experience shows that the investment pays for itself within a very short time.

Curious? Then use the opportunity now to test GoSpeech for free.

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