![\"Speech](\"https:\/\/www.clickworker.de\/wp-content\/uploads\/2021\/03\/voice-recognition-daily-life.png\")
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Over the course of the past decade, the world has gone through a radical transformation. Technologies that were once something popularized by science fiction have now become a facet of our daily life. One technology that has now become so commonplace, most don\u2019t even give it a second thought is speech recognition. <\/p>\r\n\r\n
Nowadays, AI powered voice assistants like Alexa, Siri and Google are scattered throughout our homes and smartphones – but it wasn\u2019t always this way. For quite a long period of time, voice control was very hit and miss. \r\n<\/p>\r\n\r\n\r\n
While computers have had the capability of recognizing voices for quite a while, they have not been too successful in their endeavors to understand them. Interactive Voice Response (IVR) systems around the world have simply not been able to get it right and clients on customer support lines continued to struggle. <\/p>\r\n\r\n
Recently, however, that has started to change. Thanks to the growth of Artificial Intelligence (AI) as well as Natural Language Processing (NLP) technologies, error rates with speech recognition are dropping. Now close to 95% accurate, the technology is finally starting to pay dividends in terms of usefulness and utility. <\/p>\r\n\r\n
Speech Recognition Technology is now being used across businesses and while customer service teams are benefiting greatly, its use is being seen in many other areas also. Companies are rapidly embracing speech as a means of simplifying processes and driving an increase in overall operations and efficiencies.\r\n<\/p>\r\n\r\n\r\n\r\n
Facet-rich audio datasets for training speech recognition<\/a> technologies can be ordered quickly and affordably through clickworker.<\/blockquote>\r\n\r\n\r\n\r\nHow did we get here – the history of Speech Recognition Technology<\/h2>\r\n\r\n
It\u2019s been a somewhat bumpy road to this point and we definitely did not go from zero to hero<\/em> overnight when it comes to Speech Recognition Technologies. However, the comfort we now have with voice assistants like Alexa, Siri, Cortana and Google would not be possible without the pioneers that preceded them.<\/p>\r\n\r\n
Speech has actually been something of interest since the early days of computing. In the 1950s and 60s, Bell labs worked on a system known as Audrey which could recognize single digit numbers. Ten years later, IBMs Shoebox System,<\/a> which had the ability to understand 16 words, was developed.<\/p>\r\n\r\n
Speech recognition continued to be worked on and developed in the decades that followed. In the 1970s for example, the US Department of Defense and DARPA worked on programs which eventually led to the Harpy system. Harpy, developed by Carnegie Mellon, was able to understand and respond to 1,000 words, which was a massive improvement of earlier systems. However, despite this improvement, its capabilities were still only equivalent to those of a three-year-old child.<\/p>\r\n\r\n
The 1980s and 90s continued to see gradual improvements and by the early 2000s, speech recognition had reached close to 80% accuracy. However, at this point, things seemed to stall for a little while until the latter half of the 2000s and the 2010s. <\/p>\r\n\r\n
During this period of time, Google voice, Apple\u2019s Siri and other similar technologies were being developed and deployed. It was this last push that helped transform speech capabilities and moved the needle closer to 95% accuracy. Google and others have continuously improved on what they \u201chear\u201d by using their massive data collection projects and cloud-based processing. <\/p>\r\n\r\n\r\n
How does Voice Recognition Work?<\/h2>\r\n
Speech recognition might seem simple to a lay person but in reality, it is very complex. Think about speech recognition as something similar to the way in which a child learns a language: Children hear speech around them on a daily basis. Whether it is their siblings, parents or strangers – a child is constantly absorbing different verbal and non-verbal cues. This trains their brain and builds connections between words and their meaning.<\/p>\r\n\r\n
While it may seem as if we\u2019re hardwired for language, it actually takes time and training. Speech recognition technology is essentially very similar. With computers, we\u2019re still learning how best to train them, but it is a very similar process and involves lots of effort and repetition. Perfecting speech recognition systems might be an almost impossible task with the number of languages, accents and dialects in the world today. However, we are continually getting closer.<\/p>\r\n\r\n
What are the benefits of speech recognition?<\/h2>\r\n
Advances in technology have primarily been made to simplify our lives and empower us to do more. Speech recognition is on the cutting edge of these advances and is making a huge impact to many in their day-to-day lives. There are many different benefits to Speech Recognition Technology. Some of the major benefits include:<\/p>\r\n\r\n
Control of Voice Assistants<\/h3>\r\n
Voice assistants<\/a> like Google and Alexa are now extremely commonplace on smart speakers in many homes around the world. Added to these speakers, assistants like Cortana on our computer or Siri and Google on our smartphones have quickly made voice assistants something many of us cannot live without.<\/p>\r\n\r\n
Speech recognition in Healthcare<\/h3>\r\n
Speech recognition technologies have many different roles to play in the medical field<\/a>. From a patient\u2019s point of view, speech technologies are being used to improve how patients with speech impairments communicate.<\/p>\r\n \r\n
Speech technologies are also being used by medical professionals. Doctors are using apps that can transcribe their notes during a consultation. This lets Doctors improve their focus and concentration and also improves overall record keeping. <\/p>\r\n\r\n
Speech recognition for the hearing empaired<\/h3>\r\n
Voice-to-text and transcription tools can help hard of hearing and deaf students learn in ways they were previously denied. In addition, for individuals impacted by visual impairments, text-to-speech dictation technologies and screen readers can be a crucial tool.<\/p>\r\n\r\n
Speech recognition and customer service<\/h3>\r\n
With the greater accuracy of speech recognition now available, customers are better able to use IVR systems to get their call routed correctly. Speech recognition can also help remove some of the workload from contact centers by letting chatbots answer common questions<\/a> or find answers that do not require human intervention. For questions that do require human assistance, identifying information can be obtained in advance to help speed up response times. <\/p>\r\n\r\n
Speech recognition and vehicles<\/h3>\r\n
One area where speech recognition is having a significant and life-saving impact is with vehicles. Assistant features powered through Android Auto and Apple Carplay help remove in-car distractions from drivers to keep them focused on the road.<\/p>\r\n\r\n
Now, using car infotainment systems<\/a>, drivers can send and receive texts while on the road safely, change radio stations without touching a dial and even navigate to new restaurants and landmarks simply by using their voice.<\/p>\r\n\r\n
Speech Recognition in the Workplace<\/h3>\r\n
While we\u2019d all love to have a personal assistant, sadly only a few very senior executives have access to them. Luckily digital voice assistants are now becoming a lot more mainstream. These assistants can help find files and even take meeting notes by transcribing conversations on the fly. Security can also be enhanced through the use of voice recognition instead of swipe cards.<\/p> \r\n\r\n
AI and ML in Speech Recognition<\/h2>\r\n
Artificial Intelligence<\/a> (AI) was a phrase initially coined in 1956. Since then, AI has become defined as a means of allowing computers to perform tasks and services that previously only humans were capable of. Machine Learning<\/a> (ML) is a part of AI and refers to the methods through which digital systems educate themselves. <\/p>\r\n\r\n