The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Emotion recognition in spontaneous speech using GMMs
Abstract
Automatic detection of emotions has been evaluated using standard Mel-frequency Cepstral Coefficients, MFCCs, and a variant, MFCC-low, calculated between 20 and 300 Hz, in order to model pitch. Also plain pitch features have been used. These acoustic features have all been modeled by Gaussian mixture models, GMMs, on the frame level. The method has been tested on two different corpora and languages; Swedish voice controlled telephone services and English meetings. The results indicate that using GMMs on the frame level is a feasible technique for emotion classification. The two MFCC methods have similar performance, and MFCC-low outperforms the pitch features. Combining the three classifiers significantly improves performance. 1.
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Citations
Cites
Toward detecting emotions in spoken dialogs
Lee, C. M., & Narayanan, S. S. (2005) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/tsa.2004.838534 · Cited by 988
Cited by
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.52 · Cited by 2,797
CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset
Cao, H., Cooper, D. G., Keutmann, M. K., Gur, R. C., Nenkova, A., & Verma, R. (2014) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2014.2336244 · Cited by 914
Schuller, B., Batliner, A., Steidl, S., & Seppi, D. (2011) · Speech Communication · doi:10.1016/j.specom.2011.01.011 · Cited by 758
Akçay, M. B., & Oğuz, K. (2020) · Speech Communication · doi:10.1016/j.specom.2019.12.001 · Cited by 721
Speech Emotion Recognition Using Deep Learning Techniques: A Review
Khalil, R. A., Jones, E., Babar, M. I., Jan, T., Zafar, M. H., & Alhussain, T. (2019) · IEEE Access · doi:10.1109/access.2019.2936124 · Cited by 702
Metadata
- Authors
- Neiberg, D., Elenius, K., & Laskowski, K.
- Venue
- Interspeech 2006
- Publisher
- ISCA
- Published
- 2006-09-17
- Pages
- paper 1581-Tue1A3O.5
- ISSN
- 2308-457X (ISSN-L)
- OpenAlex
- W1844030040
- Cited by
- 247
- References
- 1
- FWCI
- 21.83
- Type
- conference paper
- Language
- en
- Open access
- closed
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