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Author (up) Rajesh M. Hegde; B.S. Manoj; Bashkar D. Rao; Ramesh R. Rao pdf  isbn
  Title Emotion detection from speech signals and its applications in supporting enhanced QoS in emergency response Type Conference Article
  Year 2006 Publication Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2006  
  Volume Issue Pages 82-91  
  Keywords Feature extraction; Information systems; MESH networking; Network layers; Speech processing; Throughput; Wireless mesh networks (WMN); Emotion detection; Gmm; MAC layer; Networking; Vq; Quality of service  
  Abstract Networking in the event of disasters requires new hybrid wireless architectures such as Wireless Mesh Networks (WMNs). Provisioning Quality of Service (QoS) in such networks which are quickly deployed during emergencies demand radical solutions. In this paper, we provide a new QoS approach for voice calls over a wireless mesh networks during emergency situations. According to our scheme, the contention and back-off parameters are modified based on the emotion content in the voice streams. This paper also looks at methods for detecting emotion from an incoming voice call using the speech signal. The issues of interest in such situations are whether the caller is in a state of extreme panic, moderate panic, or in a normal state of behavior. The communication network behavior should be modified to provide differentiated QoS for calls based on the degree of emotion. We use several features extracted from the speech signal like the range of pitch variation, energy in the critical bark band, range of the first three formant variations, and speaking rate among others to discriminate between the three emotional states. At the back end the Gaussian mixture modeling techniques is used to model the three emotional states of the speaker. Since a large number of features increase the computational complexity and time, a feature selection technique is employed based on the Bhattacharya distance, to select the set of features that give maximum discrimination between the classes. These set of features are employed to simulate an emotion recognition system. The results indicate a promising emotion detection rate for the three emotions. We also present the early results on detecting the emotion content in the speech and using this in the MAC layer differentiated QoS provisioning scheme. Our scheme provides an end-to-end delay performance improvement for panicked calls as high as 60% compared to normal calls.  
  Address Department of Electrical and Computer Engineering, University of California San Diego, United States  
  Corporate Author Thesis  
  Publisher Royal Flemish Academy of Belgium Place of Publication Newark, NJ Editor B. Van de Walle, M. Turoff  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9090206019; 9789090206011 Medium  
  Track COMMUNICATION CHALLENGES IN EMERGENCY RESPONSE Expedition Conference 3rd International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 566  
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