Monaural Speech Source Separation by Estimating the Power Spectrum Using Multi-Frequency Harmonic Product Spectrum

Ayllon D, Gil-Pita R, Rosa-Zurera M. Monaural Speech Source Separation by Estimating the Power Spectrum Using Multi-Frequency Harmonic Product Spectrum. In: AES Convention 134. Audio Engineering Society; 2013. Paper 8832. Available from: https://aes.org/publications/elibrary-page/?id=16733

@inproceedings{Ayllon2013_16733,
  author = {Ayllon, David and Gil-Pita, Roberto and Rosa-Zurera, Manuel},
  title = {{Monaural Speech Source Separation by Estimating the Power Spectrum Using Multi-Frequency Harmonic Product Spectrum}},
  booktitle = {AES Convention 134},
  note = {Paper 8832},
  year = {2013},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16733}
}

TY  - CPAPER
TI  - Monaural Speech Source Separation by Estimating the Power Spectrum Using Multi-Frequency Harmonic Product Spectrum
AU  - Ayllon, David
AU  - Gil-Pita, Roberto
AU  - Rosa-Zurera, Manuel
T2  - AES Convention 134
M1  - Paper 8832
PY  - 2013
DA  - 2013/05/06
UR  - https://aes.org/publications/elibrary-page/?id=16733
PB  - Audio Engineering Society
LA  - en
AB  - This paper proposes an algorithm to perform monaural speech source separation by means of time-frequency masking. The algorithm is based on the estimation of the power spectrum of the original speech signals as a combination of a carrier signal multiplied by an envelope. A Multi-Frequency Harmonic Product Spectrum (MF-HPS) algorithm is used to estimate the fundamental frequency of the signals in the mixture. These frequencies are used to estimate both the carrier and the envelope from the mixture. Binary masks are generated comparing the estimated spectra of the signals. Results show an important improvement in the separation in comparison to the original algorithm that only uses the information from the HPS.
ER  -