What is data transcription and how to use it in your ML projects?
Find out all about data transcription and how machine learning is making it easier.
It is the act of converting speech from audio or video files to text for documentation or qualitative analysis. It gives room for the transcriber to put himself within the context of the speech.
It is the method of transcription which records every aspect of the speech as it sounded. Whether there is a pause, a stutter, a slang, or an interjection, everything is recorded. It requires no effort to cover up errors or repetitions.
With this method, the verbatim speech is formalized and edited in a clarified and concise manner. It takes certain things including grammatical errors, incomplete sentences and slang into account.
It is the thoroughly cleaned-up version of the verbatim speech. The non-functional words, sounds and expressions are removed. Grammatical errors are taken into consideration. To convey the exact intended meaning, paraphrasing may come in.
Machine learning makes use of voice and speech recognition software which converts the files to text format.
The medical history of patients is recorded, but is a time-consuming process for medical professionals. Doctors dictate among others, the summary of consultations, patient reports, and surgical procedures. The audio files are converted to text using speech-to-text softwares.
The text-to -speech software is used to transcribe musical lyrics. In addition, it is used for movie subtitles. News channels also transcribe dialogues that come up during interviews or documentaries for future-proof or clarity.
During legal proceedings, there is a voluminous amount of interrogations, responses, interjections and dialogues. For the sake of evidence, disambiguation and future litigation which may drag for years, transcription is used. It also helps legal officers who are unable to keep up with the speed of proceedings at the court.
Manual transcriptions are very time consuming and tiring. Artificial Intelligence makes use of Natural Language Processing to transcribe data in minutes. It is very useful in situations where the voice data is very voluminous.
The machine learning softwares used for transcription has the ability to detect chronological order of events and the various speakers. It allows users to identify vital portions of lengthy audio files and create soundbites.
Companies can integrate their software programs with machine learning models to automatically send transcription data to their project management and customer relations tools.
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