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Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
Its training dataset consisted of Arabic and English, some containing computer code. [ 1 ] [ 3 ] According to Timothy Baldwin, provost, and professor of natural language processing at MBZUAI, training the model on a diverse Arabic dataset allows it to switch between dialects.
Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.
Zamzar is an online file converter and compressor, created by brothers Mike and Chris Whyley in England in 2006. [1] [2] It allows users to convert files online, without downloading a software tool, and supports over 1,200 different conversion types. [3]
Otter.ai was founded as AISense in 2016 by Sam Liang and Yun Fu, two computer science engineers with a long history of working with artificial intelligence. [ 2 ] [ 3 ] In January 2018, the company announced a partnership with Zoom Video Communications to transcribe video meetings post-conference. [ 4 ]
The first Arabic language analyst for the project was a BYU undergraduate student named Derek Foxley, hired as part-time. Foxley was in 4th year Arabic courses at the time at BYU. [1] Tim Buckwalter was employed several months later as a full-time employee of ALPNET. Buckwalter was also a PhD candidate in Arabic at the time.
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The use of speech recognition is more naturally suited to the generation of narrative text, as part of a radiology/pathology interpretation, progress note or discharge summary: the ergonomic gains of using speech recognition to enter structured discrete data (e.g., numeric values or codes from a list or a controlled vocabulary) are relatively ...