With the present advancements in technology, automated transcription has improved greatly in quality standards. With how cheap these transcripts are available, they are sought after a lot by various companies for their transcription needs.
But there is still one thing that remains a constant, and that is that they always remain less professional than manual transcripts; thereby failing to meet the client’s expected quality and accuracy benchmarks.
This is because automated software can’t pick out slurred speech, heavy accent and muffled or garbled voices very well. And that results in a low accuracy rate.
In this blog, we aim to tell you everything that you need to know about why manual transcription is better than automated transcription and why you should choose it for your transcription needs.
Quality Transcription Service is within your budget now as Servixer is excited to offer this with unmatched affordability.
The issue with Al transcription software.
AI-powered transcription is done based on the understanding of the application used for transcribing files as well as their historical knowledge about the language and speech. However, in practical terms, all these applications struggle in performing their task, no matter how advanced the learning approach they integrate for the transcription process.
Some of the common reasons that make human-powered transcription better than AI-powered transcription are:
- Understanding Background noise.
If you are employing automated transcription for your audio files. You must make certain that the file that you are providing to be transcribed is clean, meaning it doesn’t contain background noise and is clear of slurred or muffled speech as AI cannot distinguish between background noise and actual speech.
If you have a file containing any background noise (like music, wind in a moving car, traffic, or background conversations as in courtroom proceedings) then you should be employing manual transcription as a human transcriber can distinguish between actual speech effectively. Thus, manual transcribers deliver a much better and quality transcript.
Since it’s practically impossible to get perfect conditions for recording audio all the time, you should opt for human transcription.
- Multiple Speakers
Speech to text conversion software is effective when there is only one speaker in a recorded audio file. However, when it comes to audio files containing many speakers then it becomes hard for AI softwares to detect them properly.
A group conversation (like legal proceedings, focus groups, interviews, panel discussions, etc.) is completely different from a recording by a single person. Some of the common differences can be:
- one speaker might be louder than the other,
- one speaker might interrupt the other one in between their statement, or
- Sometimes more than one person might speak simultaneously to make their point
These issues directly impact the quality of transcription done by automated transcription.
- Multiple Accents
If you want a transcript for a file that contains speaker with accent than it is crucial that you employ manual transcription service. The reason why manual transcript is better than Al-powered transcript in this matter, is because AI-powered transcripts aren’t made to recognize different accent.
Take for instance, English is spoken all over the world and therefore, it’s spoken in many different accents. It is hard, dare I say impossible to encrypt all kinds of accents to be detected by a computer.
A manual transcriber can focus better on understanding accents and therefore, can give better quality transcripts than AI-powered transcriptions.
Though the transcription industry is facing intense competition from AI-powered transcription apps. In the past few years, innovation in AI & ML helped enhance the quality of transcribed audio. Still, for quality intensive transcription jobs, AI has a long way to go. Even if the AI-powered apps deliver better quality, they must go through a manual quality check to make sure the final transcript is good to go. Therefore, humans are still more effective in delivering quality results in transcription compared to AI-based apps.
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