Standard audio transcription services have been ever evolving since the first speech recognition experiments took place more than 50 years ago. These culminated in the invention of the telephone as we know it today, but they unknowingly started an area of audio research that has continued ever since.
From this time, we have seen huge advancements in voice recognition, computing and digital technology which has put us on an exponentially expanding path of possibilities for the future of voice recognition audio transcription services. There is current confliction within the market place whether the manual transcription service will ever become redundant and replaced by the appearance of AI (artificial intelligence) or if human interaction will remain forever needed.
We can see that as we have progressed through more modern times, especially since the birth of home computers in the 90’s the big players in this market have been testing and improving voice recognition software consistently. Each time striving for improvements on the previous releases, with the aim of perfection in their results. If this was achieved this would allow for a fully automated service to be confidently released and rolled out. But have we got there? and what is the actual future of audio transcription services when placed against the advancements of machine learning and artificial intelligence?
Thankfully, audio transcription services are currently managing to hold onto a good share of the market, still providing a service predominately carried out by the human senses, as it is has become apparent that even though we have seen exciting advancements in artificial voice recognition, (commonly witnessed in the modern home with of Alexa or Google virtual assistants and also in call centres often unknowingly manned by automated voice programmes) these technologies have their downfalls. These problems have ben realised as machine learning occurs by ‘listening’ to a standard voice that a computer programme can learn to recognise over a period of time. However, when variances to this standard are given to the computer, it can fail to recognise what is being said and therefore leave the resulting translations open to errors. Ask your home assistant a question in a strong regional accent and I can almost guarantee you won’t be understood.
This is why humans will always have the upper hand on technology. We possess the intelligence to understand many different nuances of language, slang words, emotions and even different speeds and tones of vocal sounds. This is a hugely important factor when we you are looking to transcribe from audio to text a professional document, maybe a university journal, a technical specification, doctors and surgical notes or legal documentation. The margin for error in these cases is zero percent with nothing less than one hundred percent accurate being deemed acceptable. Which is why human intervention will always be required. We can be rest assured that we have our human intuition, senses and intelligence to correct the errors the machines cannot, and we can provide the accuracy and consistency needed when dealing with nuances of accents, voice flexion and accentuation and noise disturbances.