Transforming speech into text transcription has revolutionized the way businesses document, preserve and leverage their content. Organizations are rapidly waking up to the opportunity of this rich data resource, especially with regard to usability and effectiveness as a source of insight.
Pathways to transcription have advanced and today several different forms of transcription are available to accommodate a wide variety of needs, use cases and requirements.
This article will touch on the various transcription types, so you can better understand their core differences and consider the best model of transcription to leverage for your own unique purpose.
Understanding Various Transcription Types
In recent years, we have witnessed a dramatic evolution of transcription as a service. Organizations around the globe are leaning more heavily upon transcription, for a wide variety of reasons, ranging from compliance through to operational insight and commercial advantage.
Historically, transcription was a painstakingly manual procedure, but the process is increasingly being shaped by advancing technologies, intelligent AI and machine learning. In the U.S. alone, the transcription market size was valued at $19.8 billion in 2019 and is now expected to have a 6.1% increase by 2027.
However, not all transcription services are created equally. In certain circumstances, a very specific model of transcription may be required, for example, to meet certain regulatory requirements or compliance parameters, or simply to access the most cost-effective process.
Businesses need to familiarize themselves with a wide variety of transcription technologies and techniques, especially if they are working within heavily regulated industries.
Which Model Of Transcription Is Best?
Transcription is not an exact science. Each model of transcription has its set of challenges and advantages, so suitability depends on each individual use case. Although some transcription types are certainly more common than others, there is no one “golden standard”.
Still, in some circumstances, a certain form of transcription will be essential. For example, in verbatim transcription, word for word accuracy is of paramount importance. In others, an edited form of transcription will deliver a more impactful result.
Ultimately, if you want to make a decision on the best transcription model, you need to have your organizational objectives crystal clear. The best transcription model is one that comes closest to fulfilling the requirements of the specific goals you are looking to achieve through the process, at a pace – and price – that is acceptable.
What Is Verbatim Transcription?
Verbatim transcription offers a word-for-word reproduction of spoken data. It is an accurate type of transcription, as it captures everything verbally said, including incomplete sentences and interjections. This can be invaluable – for example, in some situations, a high cadence of hesitation could carry a huge amount of implied meaning – what’s not being said could be just as important as what is…
Technically, this model of transcription can be manual or automated with the use of artificial intelligence technology. Verbatim transcription tends to represent a good fit when regulatory compliance is necessary, as it is absolutely accurate and it takes away the need for subject expertise if human input was to be applied.
On the other hand, this model can be hard to read and difficult to obtain adequately accurate results from an automated process. Although sometimes interjections can give important contextual clues, the transcription might be full of “ums” and “ahs” which make interpretation tedious. Manual verbatim transcription can, understandably, also be very costly.
Some areas where verbatim transcription is preferred or required would be research interviews, law enforcement recordings and documentation of court proceedings.
What Is Edited Transcription?
Edited transcription is a complete and accurate script, edited to meet readability, conciseness and clarity standards. This model polishes the document to address issues arising from literal transcription, such as grammatical errors, slang, interjections and incomplete sentences.
One of the benefits of edited transcription is that the resultant document tends to be more accessible and allows a higher level of understanding. With this model, you are aiming to convey the general sense and drive of the piece, as opposed to attaining perfect accuracy.
There is, however, a risk of paraphrasing and losing important nuances in the edited transcription. Organizations must be more attentive in having a deeper comprehension of the topic, as it needs to be a trustworthy representation of the original speech.
Edited transcription is often used when content needs to be transcribed and published. Some practical examples are foreign language transcriptions, academic lectures, conferences and media interviews.
What is Intelligent AI Transcription?
Intelligent AI transcription uses AI speech recognition technology to turn spoken word and audio data into transcribed text.
This advanced type of transcription can seamlessly interpret human speech and transform it into a highly accurate text form. Intelligent AI is very cost-effective for businesses, reducing manual input, including possible errors and misinterpretation.
However, the human side should not be underrated. Emotions are part of the way we converse as humans, so a human-free transcription can struggle to interpret important contextual information or even misrepresent the tone of the discussion or speech.
Some examples of areas where intelligent AI transcription may be required or preferable are market research, agent performances and video subtitling. Overall, this model of transcription is ideal when analyzing large volumes of audio when general patterns are being picked out.
Finding the best model of transcription
There are many transcription types available for organizations, each with its own pros and cons. The best way to find out what is the best fit for your needs is to clarify in which situations you will need the transcription the most. This way, it is easier to identify which model is the most suitable for your individual requirements.
For many use cases, a hybrid verbatim / intelligent AI transcription is ideal, as it factors in a “Human In The Loop” stage – giving the best of both worlds. This model of transcription is also the most cost-effective, as it empowers organizations to generate automated transcription at scale, with the opportunity to add the all-important context of a human touch in a tactical and affordable manner.