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Databases, features and classifiers for speech emotion recognition: a review

Swain, Monorama, Routray, Aurobinda, Kabisatpathy, P.·2018·International Journal of Speech Technology
DOI 10.1007/s10772-018-9491-z
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Cited by

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Metadata

Authors
Swain, M., Routray, A., & Kabisatpathy, P.
Venue
International Journal of Speech Technology
Publisher
Springer Science and Business Media LLC
Published
2018-01-19
Volume
21
Issue
1
Pages
93-120
ISSN
  • 1381-2416 (ISSN-L)
  • 1572-8110
DOI
10.1007/s10772-018-9491-z
OpenAlex
W2784665486
Cited by
356
References
17
FWCI
34.86
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)

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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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CoChat. (2026). Citation check: Databases, features and classifiers for speech emotion recognition: a review. https://app.cochat.ai/papers/10.1007/s10772-018-9491-z
The paper
Swain, M., Routray, A., & Kabisatpathy, P. (2018). Databases, features and classifiers for speech emotion recognition: a review. International Journal of Speech Technology. https://doi.org/10.1007/s10772-018-9491-z

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.