Comparative study of voice conversion framework with line spectral frequency and Mel-Frequency Cepstral Coefficients as features using artficial neural networks

@article{Bhuyan2015ComparativeSO,
  title={Comparative study of voice conversion framework with line spectral frequency and Mel-Frequency Cepstral Coefficients as features using artficial neural networks},
  author={Amit Kumar Bhuyan and Jagannath H. Nirmal},
  journal={2015 International Conference on Computers, Communications, and Systems (ICCCS)},
  year={2015},
  pages={230-235}
}
This paper is intended to formulate the mapping function using Feed-forward Neural Networks on Line Spectral Frequency and Mel Frequency Cepstral Coefficient and to compare their outcomes to decipher the better solution to the spectral mapping impediment. The experimentation is confined to the augmentation of spectral and excitation (glottal) domains of speech. LSF and MFCC are used to represent the spectrum and as input predictor variables to the above mentioned neural networks. It contains… CONTINUE READING

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