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pro vyhledávání: '"Shriberg, Elizabeth"'
We propose a novel multi-task pre-training method for Speech Emotion Recognition (SER). We pre-train SER model simultaneously on Automatic Speech Recognition (ASR) and sentiment classification tasks to make the acoustic ASR model more ``emotion aware
Externí odkaz:
http://arxiv.org/abs/2201.11826
Akademický článek
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Publikováno v:
In Speech Communication 2010 52(3):236-245
Autor:
Shriberg, Elizabeth
Publikováno v:
Journal of the International Phonetic Association, 2001 Jan 01. 31(1), 153-169.
Externí odkaz:
https://www.jstor.org/stable/44645157
Autor:
Piotr Chlebek, Ricardo C. L. F. Oliveira, Y. Lu, Amir Harati, Tomasz Rutowski, Shriberg Elizabeth E
Publikováno v:
2020 IEEE Signal Processing in Medicine and Biology Symposium (SPMB).
Depression is a global health concern with a critical need for increased patient screening. Speech technology offers advantages for remote screening but must perform robustly across patients. We have described two deep learning models developed for t
Autor:
Tomasz Rutowski, Yang Lu, Ricardo C. L. F. Oliveira, Piotr Chlebek, Amir Harati, Shriberg Elizabeth E
Publikováno v:
UbiComp/ISWC Adjunct
Behavioral health conditions such as depression and anxiety are a global concern, and there is growing interest in employing speech technology to screen and monitor patients remotely. Language modeling approaches require automatic speech recognition
Publikováno v:
In Computer Speech & Language 2006 20(4):468-494
Publikováno v:
In Speech Communication 2000 32(1):127-154
Autor:
Shriberg, Elizabeth1 ees@speech.sri.com, Bates, Rebecca2, Stolcke, Andreas1, Taylor, Paul3, Jurafsky, Daniel4, Ries, Klaus5, Coccaro, Noah4, Martin, Rachel6, Meteer, Marie7, Van Ess-Dykema, Carol8
Publikováno v:
Language & Speech. Jul-Dec98, Vol. 41 Issue 3/4, p443-492. 50p.
Autor:
Shriberg, Elizabeth E.1
Publikováno v:
Language & Speech. Jan-Jun92, Vol. 35 Issue 1/2, p127-136. 10p.