Multi-algorithm Fusion for Speech Emotion Recognition

  • Gyanendra K. Verma
  • U. S. Tiwary
  • Shaishav Agrawal
Part of the Communications in Computer and Information Science book series (CCIS, volume 192)


In this paper, we have proposed a speech emotion recognition system based on multi-algorithm fusion. Mel Frequency Cepstral Coefficients (MFCC) and Discrete Wavelet Transform (DWT), the two prominent algorithms for speech analysis, have been used to extract emotion information from speech signal. MFCC, a representation of the short-term power spectrum of a sound is a classical approach to analyze speech signal whilst the DWT, a multiresolution approach mainly approximate the frequency information along with time information. Feature level fusion of algorithms has been performed after extraction of features by acoustic analysis of speech emotion signal. The final emotion state was determined by classification using Support Vector Machine. Popular Berlin emotion database is used for evaluation of the proposed system. The results achieved are very promising as the proposed fusion algorithm performed well compared to individual algorithms.


Multi-algorithm Fusion MFCC DWT Speech Emotion Recognition 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Gyanendra K. Verma
    • 1
  • U. S. Tiwary
    • 1
  • Shaishav Agrawal
    • 1
  1. 1.Indian Institute of Information Technology, AllahabadAllahabadIndia

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