Results 221 to 230 of about 2,908 (266)

Detecting Alzheimer’s Disease by Exploiting Linguistic Information from Nepali Transcript

2020
Alzheimer’s disease (AD) is the most common form of neurodegenerating disorder accounting for 60–80% of all dementia cases. The lack of effective clinical treatment options to completely cure or even slow the progression of disease makes it even more serious.
Surendrabikram Thapa   +5 more
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Linguistic and motor constraints on the timing of transcription

1980
This item was digitized as part of a project to share McGill's intellectual legacy with the public. If you are the copyright holder or a relative of the copyright holder who is deceased, you may request withdrawal by emailing escholarship.library@mcgill.ca.
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Meta Data Extraction from Linguistic Meeting Transcripts for the Annodex File Format

11th International Multimedia Modelling Conference, 2005
Semantic interpretation of the data distributed over the Internet is subject to major current research activity. The Continuous Media Web (CMWeb) extends the World Wide Web to time-continuously sampled data such as audio and video in regard to the searching, linking, and browsing functionality.
Claudia Schremmer, Silvia Pfeiffer
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Mode-switching in video-mediated interaction: Integrating linguistic phenomena into multimodal transcription tasks

Linguistics and Education, 2021
Abstract Digital environments have shaped unprecedented configurations of spontaneous interactions ( Herring, 2013 ), thus giving rise to emergent patterns of language variation. The borders between spoken and written language have been blurred by the interplay of semiotic resources and medium affordances ( Kress & van Leeuwen, 2001 ), and to the ...
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Evaluation of Linguistic Properties of Synthesized Laughter Using its Transcription

2022 IEEE 11th Global Conference on Consumer Electronics (GCCE), 2022
Noritake Suto, Kazuhiro Kondo
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Data Quality Relevance in Linguistic Analysis: The Impact of Transcription Errors on Multiple Methods of Linguistic Analysis.

2019
There is an enormous amount of recorded speech generated daily, and quickly transcribing and analyzing the text of this speech could have tremendous value to organizations and researchers. However, the speech transcription process has historically been laborious, expensive, and slow. Automatic speech recognition (ASR) tools have matured a great deal in
Pentland, Steven   +3 more
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