{"id":58692,"date":"2021-05-05T07:00:32","date_gmt":"2021-05-05T06:00:32","guid":{"rendered":"https:\/\/www.clickworker.com\/?p=58692"},"modified":"2022-07-25T16:09:58","modified_gmt":"2022-07-25T15:09:58","slug":"development-of-speech-recognition-systems","status":"publish","type":"post","link":"https:\/\/www.clickworker.com\/customer-blog\/development-of-speech-recognition-systems\/","title":{"rendered":"Development (history) and applications of speech recognition systems"},"content":{"rendered":"
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Walking into many houses around the world, you\u2019re likely to find one or perhaps more ubiquitous little speakers, scattered around. For the residents of these homes, these devices have become a key part of their lives, sharing details about meetings, travel plans, grocery lists and even weather reports. We\u2019ve come to depend on them to help simplify our lives and entertain us.<\/p>\r\n\r\n\r\n
However, smart speakers weren’t the first introduction of speech recognition. With Apple and Siri, speech recognition took a huge leap forward in the early 2010\u2019s, helping us get to where we are now. However, this technology didn’t happen overnight. Rather, it is something that’s been in progress for decades. <\/p>\r\n\r\n
Language and speech go back thousands of years. Conversely, computing is a much more recent development. Speech recognition software, or speech recognition technology, is an attempt to marry these two together so that computing devices can understand and react to human voice.<\/p>\r\n\r\n
Speech recognition is, however, incredibly complex. When a child is educated, they learn by watching and listening to all of the different noises around them. Over time, they associate different sounds with words and specific items. Their brain builds unique patterns that they carry with them throughout their lives, helping decipher accents, inflection and tone to provide meaning.<\/p>\r\n\r\n
Training a computer is similar in some ways, but also very different. Humans seem to learn languages effortlessly, but that is primarily because we’ve learned how best to teach children. We do not yet have that same insight with computers. What we do know is that educating machines requires data and lots of research.<\/p>\r\n\r\n
While we\u2019ve made significant strides in improving the accuracy rate of speech recognition systems, there is still work to be done to better help computers understand different dialects and languages. Today, speech recognition works fairly well for most common tasks. In fact, companies like Google and IBM state that their algorithms for speech are close to 96% accurate \u2013 but getting to this point took time and effort.<\/p>\r\n\r\n\r\n
Tip<\/strong><\/p>\r\n
Just ask clickworker to get thousands of voice recordings in the languages and dialects you need to train your speech recognition system to perfection.<\/p>\r\n Get more information about the service audio datasets<\/a> <\/blockquote>\r\n\r\n
The History of Speech Recognition systems<\/h2>\r\n
The first true speech recognition system was developed in the early 1950s. This system, called \u201cAudrey\u201d, was developed by Bell Laboratories<\/a> and focused on understanding numbers. In the following decade, IBM came out with a system that could respond to 16 words, called \u201cShoebox\u201d.<\/p>\r\n\r\n