In this smart world of today, technology has been fully integrated into our businesses and another innovation that is joining the ranks is Artificial Intelligence (AI). AI, as it is more commonly referred, has been developed to reduce the need for manpower and increase work efficiency for many processes – including data transcription.
The Process of Transcription
First and foremost, data transcription is a valuable component in research. It is primarily defined as the act of producing a textual or written account of audio and visual recordings.
The primitive way will be having someone to listen to the audio and pen it down onto paper. This process of listening to a 60mins audio could mean days to transcribe. With AI, it is just simply uploading the recordings into the system and while you are back from the kitchen with your coffee, the transcription should be sitting in your inbox for your viewing. It is just a matter of minutes.
Transcription may require rephrasing of some sentences to make the statements more cohesive. However, transcribing is straightforwardly technical, and it entails a verbatim or word-for-word approach.
Transcription services are often utilized in medical, research, academic and legal institutions to assist the transformation of audio to documents and the industries are not exhausted yet.
Role of Artificial Intelligence in Transcription
Transcribing data that is predominantly done manually, typing or writing what they hear. This requires a shift when the influx of information and the demand of outputs are steadily increasing over time.
While job markets supply enough manpower, some companies are starting to invest in more automated systems. AI fits into the process of transcription since it fuels the process with more speed to accommodate its growing demand from many enterprises and institutions.
Transcription requires speed and accuracy for the outputs to be of use. It is also a process that involves the transfer of data with little to no room for error, thus classifying it as work defined by a structure or a set of rules. This is where compliance intelligence, or CI, comes in. It is done through automated transcription, which relies on ASR or automatic-speech-recognition software. This allows for transcription to be done live or pre-recorded, thus making the content more inclusive and accessible. The parameters of rules will be pre-set into the software which will comply with the enterprise or institution requirements.
What is Compliance Intelligence?
This branch of artificial intelligence focuses on “compliance”, which is defined by the capability to follow particular steps in established structures involving rules, regulations and restrictions. With that, Compliance Intelligence (CI) is associated with the analysis of information, its application to a system, and its reaction to changes, parameters and violations.
CI in data transcription also incorporates the use of ASR engines with fixed parameters to allow for live, recorded, onsite or offsite processing. With that, it can make data transcription work more cost-efficient, time savvy and productive. Such innovation can benefit businesses and institutions for example in insurance, that need constant monitoring. Industry-specific software could be developed through specific training data with pre-set rules to transcribe information.
Advantages of Compliance Intelligence in Data Transcription
This approach towards CI comes with the promise of many benefits that exceed what normal AI transcription can provide.
1. Minimal Manual Input
Given that CI data transcription is designed with autonomous technology with the specific rules, the need for physical manpower to check for compliance will be reduced significantly. Imagine having to go through a load of 8 hours recording, the needed focus and time will be way more than 8hours. This added feature will be automated and transcribed with keywords being made prominent for the eyes if needed for checking. This will not only save time but also maximize productivity for otherwise tedious processes.
2. Addresses Human Error
As mentioned, transcribing manually is a time-consuming task and requires lots of concentration. Human error can result from poor due diligence, ineffective processes and even outdated technology. CI has become effective in ensuring that these human errors are addressed.
3. Accurate Data Consolidation
As a business owner, you want to ensure that all the relevant workflows are in compliance. You can easily ensure this by using a CI-driven approach transcription. CI in data transcription helps you to fully comply with the compliance requirements in a timely and accurate manner. You can consolidate data accurately and organise them to help you make refined decisions.
4. Markers on Data to Facilitate Suggestions and Predictions
Onsite and live audio or recordings can give markers at certain points by the CI system to indicate significant portions, or sensitive information. This can be done by setting parameters and outlines for compliance intelligence systems to follow. Recorded data may then be analyzed to predict market outcome and engagement.
5. Monitored Vocabulary and Automated Responses
This feature can not only make business engagements efficient and productive, but it also creates filters that can facilitate data segregation. It is also incredibly helpful when analyzing and evaluating outcomes, as well as possible risks or liabilities that may involve a certain community or demographic.
That being said, we can conclude that the integration of compliance intelligence into the process of data transcription is highly beneficial. Not only does it generate better and more accurate data transfers from audio to text, but it can also help produce detailed and genuine analysis and evaluations that can help business enterprise and institutional environments.
If you’re looking to have recordings or live events tracked in accordance to your organization or government regulations, we recommend you to try the latest compliance intelligent transcription software, so you can experience the benefits for yourself.