Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods

@inproceedings{Zahid2015OptimizedAC,
  title={Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods},
  author={Saadia Zahid and Fawad Hussain and Muhammad Rashid and Muhammad Haroon Yousaf and Hafiz Adnan Habib},
  year={2015}
}
  • Saadia Zahid, Fawad Hussain, +2 authors Hafiz Adnan Habib
  • Published 2015
  • Computer Science
  • Audio segmentation is a basis for multimedia content analysis which is the most important and widely used application nowadays. An optimized audio classification and segmentation algorithm is presented in this paper that segments a superimposed audio stream on the basis of its content into four main audio types: pure-speech, music, environment sound, and silence. An algorithm is proposed that preserves important audio content and reduces the misclassification rate without using large amount of… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 55 REFERENCES

    Sports audio segmentation and classification

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL

    Content analysis for audio classification and segmentation

    VIEW 7 EXCERPTS
    HIGHLY INFLUENTIAL

    Comparative study of automatic speech recognition techniques,

    • M. Cutajar, J. Micallef, O. Casha, I. Grech, E. Gatt
    • IET Signal Processing,
    • 2013
    VIEW 7 EXCERPTS
    HIGHLY INFLUENTIAL

    Audio signal segmentation algorithm,

    • C.-C. Huang, J.-F. Wang, D.-J. Wu
    • U.S. Patent No. 7,774,203,
    • 2010
    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    Artificial Neural Network

    VIEW 1 EXCERPT