{"id":11570,"date":"2023-01-17T23:09:00","date_gmt":"2023-01-17T23:09:00","guid":{"rendered":"https:\/\/generaltranscriptionworkfromhome.com\/blog\/?p=11570"},"modified":"2025-05-24T21:37:18","modified_gmt":"2025-05-24T21:37:18","slug":"is-speech-recognition-software-affecting-transcription-jobs","status":"publish","type":"post","link":"https:\/\/generaltranscriptionworkfromhome.com\/blog\/is-speech-recognition-software-affecting-transcription-jobs\/","title":{"rendered":"Is Speech Recognition Software Affecting Transcription Jobs?"},"content":{"rendered":"
\n

If you're interested in transcription work, you may be concerned that speech recognition or voice recognition software may affect transcriptionist jobs.<\/p>\n

Speech recognition allows you to dictate into a computer and instantly create an electronic document. But even with improved speech recognition technologies available today, transcriptionists have not become obsolete.<\/p>\n

And yes, electronic medical records have reduced work for medical transcriptionists. But voice recognition is not taking away any jobs in general transcription.<\/p>\n

There are several problems with using voice recognition for transcription.\u00a0 Here are some of the reasons why voice recognition is not perfect for transcription.<\/p>\n

1. Voice recognition software requires training.<\/strong><\/h3>\n

The software must be trained to a particular speaker. People have a variety of accents, pronunciation, speaking styles and pitch differences. No two speakers say the same word exactly the same way. This is a challenge for speech recognition. Many doctors and business owners don't want to spend the time to learn and train the voice recognition software.<\/p>\n

2. Voice recognition requires more precise dictation than the way most people are used to dictating.<\/strong><\/h3>\n

The accuracy of a speech recognition transcript will dependent on the quality of recording and recorder. Doctors and business owners don't always dictate in perfect circumstances or in a quiet environment. They don't dictate clearly enough and don't dictate punctuation marks, new paragraph commands to get satisfactory results with voice recognition. They don't do the precise dictation needed to use voice recognition effectively.<\/p>\n

3. Business owners are not as familiar with voice recognition software as hospitals and clinics. <\/strong><\/h3>\n

They don't want to spend the time to train the program.<\/p>\n

4. Automatic voice recognition software doesn't work when there is more than one voice.<\/strong><\/h3>\n

This means that voice recognition software won't work to transcribe interviews and group recordings.<\/p>\n

5. Voice recognition doesn't work well when the dictator is not speaking in the microphone directly.<\/strong><\/h3>\n

For example, transcribing lectures won't work well with speech recognition.<\/p>\n

6. The transcripts from speech recognition are not accurate enough.<\/strong><\/h3>\n

Voice recognition transcripts need editing. This has created new jobs for transcription editors and some transcribing jobs have turned into transcription editing jobs both for general transcription and medical transcription.<\/p>\n

The software does not understand the context. For example, it is the context that allows you to
\ndistinguish “your” from “you're, “its” from “it's” etc.<\/p>\n

Voice recognition may change the way transcription work is done, but a real person who can think and make decisions will always be needed to verify the voice recognition results.<\/p>\n

Transcriptionists should not worry about voice recognition taking their jobs. There is plenty of work for transcriptionists and there will be plenty of work in the future.\u00a0 Voice recognition has actually created new jobs for transcription editors.=<\/p>\n

Career Step mentions that “A growing number of medical transcription editors are needed to amend patients' records, edit documents from speech recognition systems, and identify discrepancies in medical reports.”\u00a0\u00a0<\/span><\/p>\n<\/div>\n

Transcription Resources<\/strong><\/h3>\n
\n