Identification of correlation between blood relations using speech signal

@article{Padmini2017IdentificationOC,
  title={Identification of correlation between blood relations using speech signal},
  author={P. Padmini and Shikha Tripathi and K. Bhowmick},
  journal={2017 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES)},
  year={2017},
  pages={1-6}
}
  • P. Padmini, Shikha Tripathi, K. Bhowmick
  • Published 2017
  • Mathematics
  • 2017 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES)
    • This paper presents a study of how speech features have comparable parameters amongst blood relations. Mel Frequency Cepstral Coefficients (MFCC) has been used for extracting the features of input speech signal, along with vector quantization through modified k-means LBG (Linde, Buzo, and Gray) algorithm are implemented to analyse and estimate the similarity to perform related studies. The study is concentrated on database using 12 families from which voice databases were collected from all… CONTINUE READING
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