You might expect voice recognition technology to be in line for replacing audio transcription given the nature and design - however few transcription companies are worried that this relatively new technology can outperform the trained ears and skilled hands of a long-standing transcription company.
With more than a decade behind voice recognition technology, it still fails to perform in commercial settings that require a 98% success rate. The biggest issue is on the quality of the transcription, and when it comes right down to it, quality is always an important factor.
The Need for Quality Audio Transcription
Some industries put a great deal of importance on audio transcription. When you get into legal matters where accuracy is a must, the life of an individual can be at stake if words aren't transcribed verbatim. Situations like depositions, court hearings, affidavits, 911 calls, briefings, etc. all need to be as accurate as possible.
Voice recognition software can be accurate, but a number of factors can ruin the quality and accuracy of the transcription. Things like loud ambient noise, rapid speech, thick accents, slurring, poor quality recording equipment and more can result in garbled text.
Media companies have attempted to use voice recognition for years in order to produce closed-captioning of televised events and TV shows. Some still do. These systems can have a difficult time keeping up with speech and often produce captioning that lags, skips entire sentences or uses the wrong words and phrases.
A Trained Ear Can Make All the Difference with Audio Transcription
A computer can't always differentiate between speakers, and won't attempt to playback a string of audio multiple times in order to discern what a mumbled, quiet individual is actually saying. Like a new transcriptionist, they take their best guess at matching the audio to a database of similar words and then move on.
A trained transcriptionist is not only able to differentiate speakers, but they are trained to listen and pick out words through heavy accents, muffled, garbled or slurred speech and other variables.
For more difficult audio files, they even utilize software that can slightly improve the audio to make it easier to pick out individual words and phrases.
A professional transcription agency can even provide detailed audio transcription, making notes of back ground noises if desired. This can include coughing, doors opening and closing, engine starts, tapping, squeaks and other noises that could have a bearing on legal cases and investigations, corporate meetings and evaluations, 911 calls, etc.
Automated Audio Transcription in Healthcare
At one time, some healthcare providers attempted to reduce medical transcription costs by using voice recognition software. Even with physicians investing in expensive voice recognition software, early tests showed flaws in dictation and inaccurate patient notes. Medical terminology proved to be difficult and was unrecognized by the software. The result was wasted time on editing and proofing patient notes within electronic medical records. This consumed more time and cost healthcare providers more than the average investment for human audio transcription.
Why Automated Transcription Fails
Voice recognition is entirely based on algorithms that read and transform sound, matching sound patterns to a dictionary-like database. These systems are designed to read the speech of clearly spoken English. With the cultural melting pot of most countries around the world and the variations in dialect, it's simply impossible for any automated system to take the place of manual audio transcription that achieves a 99% success rate on transcribing recorded audio.