Cited by 67Sleep and Work-Related FatigueEmotion and Mood RecognitionSpeech Recognition and Synthesis

Applying multiple classifiers and non-linear dynamics features for detecting sleepiness from speech

Open access
Krajewski, Jarek, Schnieder, Sebastian, Sommer, David, Batliner, Anton, Schuller, Björn·2012·Neurocomputing

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Crossref · 10.1016/j.neucom.2011.12.021

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52 of 52 references verified0 citation errors · 0 not checkable

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Authors
Krajewski, J., Schnieder, S., Sommer, D., Batliner, A., & Schuller, B.
Affiliations
  • University of Wuppertal (DE)
  • Schmalkalden University of Applied Sciences (DE)
  • Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
  • Technical University of Munich (DE)
Corresponding author
Krajewski, Jarek
Venue
Neurocomputing
Publisher
Elsevier BV
Published
2012-05
Volume
84
Pages
65-75
ISSN
0925-2312 (ISSN-L)
OpenAlex
W2112583083
Cited by
67
References
52
Citations by year
2026: 2 · 2024: 6 · 2023: 7 · 2022: 3 · 2021: 5 · 2020: 4 · 2019: 3 · 2018: 2 · 2017: 4 · 2016: 3 · 2015: 6 · 2014: 10 · 2013: 9 · 2012: 3
FWCI
12.00
Type
journal article
Language
en
Open access
Locations
  • Neurocomputing (publishedVersion)
  • mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion, other-oa)
  • OPUS (Augsburg University) (submittedVersion, cc-by-nc-nd)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and Work-Related Fatigue
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
  • Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
Keywords
sleepiness detection, phonetic features, Karolinska Sleepiness Scale, sleep deprivation, vowel phonation, ensemble classifiers, feature selection, gender differences, phase space reconstruction, embedding dimension

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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