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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Rieger, S.A. Muraleedharan, R. Ramachandran, R.P. |
| Copyright Year | 2014 |
| Description | Author affiliation: Electr. & Comput. Eng., Rowan Univ., Glassboro, NJ, USA (Rieger, S.A.; Ramachandran, R.P.) || Electr. & Comput. Eng., Saginaw Valley State Univ., Saginaw, MI, USA (Muraleedharan, R.) |
| Abstract | Security (and cyber security) is an important issue in existing and developing technology. It is imperative that cyber security go beyond password based systems to avoid criminal activities. A human biometric and emotion based recognition framework implemented in parallel can enable applications to access personal or public information securely. The focus of this paper is on the study of speech based emotion recognition using a pattern recognition paradigm with spectral feature extraction and an ensemble of k nearest neighbor (kNN) classifiers. The five spectral features are the linear predictive cepstrum (CEP), mel frequency cepstrum (MFCC), line spectral frequencies (LSF), adaptive component weighted cepstrum (ACW) and the post-filter cepstrum (PFL). The bagging algorithm is used to train the ensemble of kNNs. Fusion is implicitly accomplished by ensemble classification. The LDC emotional prosody speech database is used in all the experiments. Results show that the maximum gain in performance is achieved by using two kNNs as opposed to using a single kNN. |
| Starting Page | 589 |
| Ending Page | 593 |
| File Size | 479252 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479942190 |
| DOI | 10.1109/ISCSLP.2014.6936711 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-09-12 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Training fusion Emotion recognition ensemble kNN classifier cyber security Cepstrum Speech recognition Speech Vectors machine learning Mel frequency cepstral coefficient emotion recognition |
| Content Type | Text |
| Resource Type | Article |
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