Audio-emotion recognition system using parallel classifiers and audio feature analyzer

L.W. Chew, K.P. Seng, L.-M. Ang, V. Ramakonar, A. Gnanasegaran

Research output: Book chapter/Published conference paperConference paper

11 Citations (Scopus)

Abstract

Emotion recognition based on an audio signal is an area of active research in the domain of human-computer interaction and effective computing. This paper presents an audio-emotion recognition (AER) system using parallel classifiers and an audio feature analyzer. In the proposed system, audio features such as the pitch and fractional cepstral coefficient are first extracted from the audio signal for analysis. These extracted features are then used to train a radial basis function. Lastly, an audio feature analyzer is used to enhance the performance of the recognition rate. The latest simulation results show that the proposed AER system is able to achieve an emotion recognition rate of 81.67%. © 2011 IEEE.
Original languageEnglish
Title of host publicationProceedings of the 2011 Third International Conference on Computational Intelligence, Modelling & Simulation
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages210-215
DOIs
Publication statusPublished - 2011
EventThird International Conference on Computational Intelligence, Modelling, and Simulation : CIMSiM 2011 - Sheraton Hotel, Langkawi, Malaysia
Duration: 20 Sep 201122 Sep 2011
https://web.archive.org/web/20110811205049/http://cimsim2011.info/ (Archived page)

Conference

ConferenceThird International Conference on Computational Intelligence, Modelling, and Simulation
CountryMalaysia
CityLangkawi
Period20/09/1122/09/11
Internet address

Fingerprint

Audio systems
Human computer interaction
Classifiers

Cite this

Chew, L. W., Seng, K. P., Ang, L-M., Ramakonar, V., & Gnanasegaran, A. (2011). Audio-emotion recognition system using parallel classifiers and audio feature analyzer. In Proceedings of the 2011 Third International Conference on Computational Intelligence, Modelling & Simulation (pp. 210-215). USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CIMSim.2011.44
Chew, L.W. ; Seng, K.P. ; Ang, L.-M. ; Ramakonar, V. ; Gnanasegaran, A. / Audio-emotion recognition system using parallel classifiers and audio feature analyzer. Proceedings of the 2011 Third International Conference on Computational Intelligence, Modelling & Simulation. USA : IEEE, Institute of Electrical and Electronics Engineers, 2011. pp. 210-215
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title = "Audio-emotion recognition system using parallel classifiers and audio feature analyzer",
abstract = "Emotion recognition based on an audio signal is an area of active research in the domain of human-computer interaction and effective computing. This paper presents an audio-emotion recognition (AER) system using parallel classifiers and an audio feature analyzer. In the proposed system, audio features such as the pitch and fractional cepstral coefficient are first extracted from the audio signal for analysis. These extracted features are then used to train a radial basis function. Lastly, an audio feature analyzer is used to enhance the performance of the recognition rate. The latest simulation results show that the proposed AER system is able to achieve an emotion recognition rate of 81.67{\%}. {\circledC} 2011 IEEE.",
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Chew, LW, Seng, KP, Ang, L-M, Ramakonar, V & Gnanasegaran, A 2011, Audio-emotion recognition system using parallel classifiers and audio feature analyzer. in Proceedings of the 2011 Third International Conference on Computational Intelligence, Modelling & Simulation. IEEE, Institute of Electrical and Electronics Engineers, USA, pp. 210-215, Third International Conference on Computational Intelligence, Modelling, and Simulation , Langkawi, Malaysia, 20/09/11. https://doi.org/10.1109/CIMSim.2011.44

Audio-emotion recognition system using parallel classifiers and audio feature analyzer. / Chew, L.W.; Seng, K.P.; Ang, L.-M.; Ramakonar, V.; Gnanasegaran, A.

Proceedings of the 2011 Third International Conference on Computational Intelligence, Modelling & Simulation. USA : IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 210-215.

Research output: Book chapter/Published conference paperConference paper

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T1 - Audio-emotion recognition system using parallel classifiers and audio feature analyzer

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AU - Gnanasegaran, A.

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AB - Emotion recognition based on an audio signal is an area of active research in the domain of human-computer interaction and effective computing. This paper presents an audio-emotion recognition (AER) system using parallel classifiers and an audio feature analyzer. In the proposed system, audio features such as the pitch and fractional cepstral coefficient are first extracted from the audio signal for analysis. These extracted features are then used to train a radial basis function. Lastly, an audio feature analyzer is used to enhance the performance of the recognition rate. The latest simulation results show that the proposed AER system is able to achieve an emotion recognition rate of 81.67%. © 2011 IEEE.

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Chew LW, Seng KP, Ang L-M, Ramakonar V, Gnanasegaran A. Audio-emotion recognition system using parallel classifiers and audio feature analyzer. In Proceedings of the 2011 Third International Conference on Computational Intelligence, Modelling & Simulation. USA: IEEE, Institute of Electrical and Electronics Engineers. 2011. p. 210-215 https://doi.org/10.1109/CIMSim.2011.44