- December 23, 2021
- by Last expert
- Blogs, Legal Transcription, Transcription
- 0 Comments
The pace with which one can speak is frequently faster than that with which one can type. Later, you may effortlessly convert an audio recording to text and communicate the information more effectively.
Why should you transcribe audio or video footage as evidence?
Important parts of the document can be underlined, and notes can be made, making a printed legal transcript superior to an audio file. This might assist attorneys in crafting inquiries or keeping track of the most crucial information in a case. It’s also easy to locate information as and when it’s needed.
Why should you transcribe depositions of court hearings?
Attorneys rely on depositions to acquire essential information for lawsuits while the witness is under oath. During depositions, attorneys frequently take notes, but the deposition transcript, which serves as a complete deposition summary, is useful to attorneys as they prepare for subsequent depositions, trials, or other legal processes.
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Drawbacks of automated transcription?
In the legal profession, high-quality transcription solutions are required, and manual transcripts are the best option. Manual transcription is also recommended for legal transcriptions such as depositions, court hearings, affidavits, 911 calls, briefings, and so on, because they must be recorded verbatim.
Problems With Automated Transcription
Some of the issues with automatic transcribing that you should be aware of when converting audio and video to text are as follows :
Limited Vocabulary
Most systems come with out-of-the-box voice recognition methodologies that are trained in broad English and do not include industry-specific, unique phrases that are utilized in the day-to-day lives of many individuals and organisations.
Accents
Many of the people that create widely used voice recognition technologies come from largely English-speaking North American organisations. This introduces a significant bias in speech recognition systems, which has a significant impact on the accuracy of automated transcription of speakers with accents and speakers who speak in other languages.
Fast Talkers
Some folks simply speak quickly. Processing is difficult for a machine. Humans can look over a transcript numerous times to make sure they understand what someone is saying, but machines are still not very good at it.
Low Audio Quality
Low-quality microphones can cause poor audio quality. While walking, people take notes. While conversing, they move around the room.
Background Noise
This is linked to poor audio quality. You will notice a significant decline in transcription accuracy if there is ambient noise, such as automobiles passing by, bangs, booms, beeps, music, or anything else.
Although systems are improving at filtering out noise, there is still a long way to go.
Overlapping Dialogue
It’s difficult to realise until you watch hours and hours of people conversing, but you rapidly learn that people enjoy talking over each other.
Our ears are amazing at interpreting this and focusing on what we need to focus on, but machines aren’t.
Technical Difficulties
Machines do not always function properly. They, too, have difficult days. Technical issues will be a major issue if you’re completely reliant on an audio-to-text converter. This can cause delays in your project deadlines if not addressed immediately.
Customization
Transcribing software cannot, of course, generate custom transcripts automatically. You’ll have to do it yourself if you want a specific format and other details (such as entering labels and punctuation) in your transcript.
Transcription Accuracy
All of this decreases the automatic transcription’s accuracy. Your final transcript will lose its professionalism as a result of this. If you’re a company that shares information online, this is critical. Furthermore, using automated transcripts for data processing can result in false positives, posing a considerable risk.
The percentage of mistake a transcript can have per word count is determined by transcription accuracy rates. For example, a transcription accuracy of 97% means there is a 3% chance of errors per every 1,000 words or about 30 errors.
A single blunder by an individual or institution might be disastrous.
Automatic transcription will not be used by most serious academic studies. They are aware of the delicate and intricate nature of language.
Automatic transcriptions can contain potentially catastrophic (and frequently tragically embarrassing) errors, depending on what you’re doing. One of my favourites was the transformation of egotistical into “eagle’s testicles.”
Despite transcription firms’ claims of data security, the risk of security breaches and unintentional content handover to law enforcement still exists. That’s why some journalists are opposed to the idea of uploading confidential interviews to a computer cloud like those used by automated transcription providers.