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ELAN is computer software, a professional tool to manually and semi-automatically annotate and transcribe audio or video recordings. [2] It has a tier-based data model that supports multi-level, multi-participant annotation of time-based media.
Transcription software assists in the conversion of human speech into a text transcript. Audio or video files can be transcribed manually or automatically. [ 1 ] Transcriptionists can replay a recording several times in a transcription editor and type what they hear.
Transcription services are often provided for business, legal, or medical purposes. The most common type of transcription is from a spoken-language source into text. Common examples are the proceedings of a court hearing such as a criminal trial (by a court reporter) or a physician's recorded voice notes (medical transcription). Some ...
Double entry (or more) may also be leveraged to minimize transcription or transposition error, but at the cost of a reduced number of entries per unit time. Mathematical transposition errors are easily identifiable. Add up the numbers that make up the difference and the resultant number will always be evenly divisible by nine. For example, (72 ...
Otter.ai, Inc. is an American transcription software company based in Mountain View, California. The company develops speech to text transcription applications using artificial intelligence and machine learning. Its software, called Otter, shows captions for live speakers, and generates written transcriptions of speech. [1]
Medical transcription, also known as MT, is an allied health profession dealing with the process of transcribing voice-recorded medical reports that are dictated by physicians, nurses and other healthcare practitioners. Medical reports can be voice files, notes taken during a lecture, or other spoken material.
For example, under such a method applied to plain English text the phrase "I run" counts as one word, but "rhinoceros" and "let's talk" would both count as two. Karat et al. found in one study of average computer users in 1999 that the average rate for transcription was 32.5 words per minute, and 19.0 words per minute for composition. [2]
3,150,000 (per sensor) Text Classification 2016 [190] T. Sztyler et al. Toronto Rehab Stroke Pose Dataset 3D human pose estimates (Kinect) of stroke patients and healthy participants performing a set of tasks using a stroke rehabilitation robot. None. 10 healthy person and 9 stroke survivors (3500–6000 frames per person) CSV Classification 2017