![]() ![]() Consistent, 100% accuracy isn’t possible for either group, but transcriptionists can still outperform speech recognition on accuracy. Accuracy is the key component of any speech recognition solution.Īlthough speech recognition accuracy has come a long way, think of it this way: speech recognition is a computer system competing with humans to better recognize human speech. Speech recognition competes with transcription on accuracy and speed. However, free automated speech recognition systems has more limitations.īeyond accessibility, there are plenty more advantages to using speech recognition, including heightened efficiency and cost savings, but there are also disadvantages to speech recognition. Some free speech recognition software also exists. Speech-to-text technology is widely accessible and speech recognition solutions designed for more specific purposes, such as legal or medical speech recognition, are also available. A transcriptionist must recognize a word, then manually type it, while speech recognition simply recognizes and instantly outputs the recognized word. Speech recognition software can be much faster than human transcription. This applies to any field – even someone with the right typing skills, which is a small enough group as it is, would not be able to easily transfer to a new field of transcription without adequate training. For example, a transcriptionist with no medical knowledge will not be able to keep up with a physician as they dictate because a typical dictation contains medical terminology that would be difficult to spell or recognize for someone with no medical background. Not only is a transcriptionist required to type quickly to efficiently convert speech to text, they must also have a working knowledge of any subject they are transcribing. They possess advanced knowledge of the terminology, the medical or legal processes, and the relationships with lawyers or doctors that, to be honest, technology is yet to have." - Ofer Tirosh, founder and CEO of translation company TomedesĪ disadvantage of transcriptionists is that the job requires a fairly unique skillset. For legal and medical transcription, for example, although there are known speech recognition tools for these fields, a human transcription has the specialized knowledge to excel in these fields. Technology is not yet as advanced as it could be, and speech recognition still makes many mistakes that human insight would not make. “While speech recognition is gaining popularity, transcriptions are here to stay, at least for now. The job requires fast typists, but even the fastest typists in the industry would have trouble competing with automated speech recognition, which can recognize and output full sentences at a time rather than needing to manually type each word. The disadvantage to the ‘human’ element of transcription is speed. A human can easily recognize words across various accents and refer to the context of a sentence to fill in any inaudible gaps – or just mark completely unrecognizable speech as ‘inaudible’.Īlthough AI can perform some of these actions with speech recognition, humans can still outperform automated speech recognition systems in accuracy. A transcriptionist is responsible for translating human speech to text. ![]() The ‘human’ element of transcription can be both an advantage and disadvantage of transcription. Many industries and organizations still prefer or continue to use transcription because of its advantages, but others have moved on because of its disadvantages. ![]() Now that speech recognition can compete with (and in many cases outperform) transcription, it is slowly being phased out. Until speech recognition became available, transcriptionists or scribes were the standard for transcribing speech. Transcriptionists listen to speech, then write or type what they hear into a written or printed format. There is also a hybrid solution, where speech recognized text is further edited by a human. In each of these applications, transcription and speech recognition could both be used to achieve similar results – but there are pros and cons to both transcription and speech recognition. Speech recognition and transcription have many applications, most prominently used for healthcare documentation, legal document creation or legal proceeding logs, and to create video transcripts for education and entertainment. Speech recognition and transcription can be used to quickly convert spoken words, numbers, or acronyms to text. ![]()
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