While speech to text has been around since the 1950s, it’s taken a long and winding path to reach the levels of accuracy it boasts today. The technology is now incorporated into almost every smart device, mainly through automatic speech recognition (ASR) employed in the voice command feature.
The real value speech to text offers us is the transformation of rich, unstructured information such as speech into data that can be measured. With machine learning, we are able to pick up on patterns that can provide us with opportunities to develop effective solutions to previously undetected problems. By next year, it is expected that 50% of all searches will be done by voice. True to the smart home device trend, 30% of those searches will be performed without a screen. The sheer volume of speech data users are creating is helping the AI-related tools we utilize to process this data become more robust at a faster rate. So, for starters, the progress we can expect with speech to text technology in the coming decade will be quicker than ever before.
Natural Language Processing: the Biggest Challenge to Progress
Even though the rate of progress is improving greatly, speech recognition is a real challenge to master simply because of how subjective speech is. Anything from background noise, to a different dialect, or even a slight speech impediment can throw off a machine’s ability to comprehend what is being said to it.
With plenty of room to grow on this front, Natural Language Processing (NLP) is a field gaining much interest and support. At present, TranscribeMe makes use of ASR to reveal insightful information about customer demographics and help businesses such as call-centers identify opportunities for growth and improvement.
As technology and its advancements make their way around the globe, there is great potential for speech to text to be of particular use in parts of the world where literacy rates are low. Where speech may be the only form of communication possible, the option to describe your symptoms to a chatbot service for medical attention would be life-changing, let alone life-saving.
Breaking Down Language Barriers and Their Time Lags
Have you ever found yourself lost in translation and, as a consequence, made the wrong decision or an irreversible mistake? We’ve all been there, and speech to text is likely to come to our rescue in relation to language barriers too. As it stands, transcription translation services are commonly available. The next generation of this cross-cultural branch would be real-time translations based on live speech. Much like science fiction movies predicted with its multi-language processor, the evolution of speech to text technology is surely headed in this direction.
Real-time translations of live speech would have a profound impact on business in today’s globalized world. Apart from increasing the reach to audiences that would normally be excluded due to language barriers, access to international markets would be improved.
Online audio and video content would also be easily translatable and replicated in other languages in addition to subtitling for greater inclusivity. Even cross-country dialogue on knowledge exchange and best-practices would benefit from facilitated communication as such. Let’s not forget the advantages the travel and tourism sector are likely to enjoy with this kind of progress.
Data Handled Smartly Will Deliver Smart Results
It is clear to see that despite any challenges, the future of speech to text holds great promise and with a particularly strong impact on business. The progress this technology is more than likely to experience in the next decade will result in its further incorporation into our everyday routines.
The expected normalization and dependence on speech to text applications highlights the growing importance of beginning to include it in your operations today. The more experience an enterprise has with this technology, the sooner it will be able to make the most of the valuable insights it can unveil and help you stay ahead of the competition.
Interested in more information on how TranscribeMe’s Automatic Speech Recognition model works? Get in touch to request a demo today!
