Marginal energy density over the low frequency range as a feature for voiced/non-voiced detection in noisy speech signals

DOI10.1016/J.JFRANKLIN.2013.01.002zbMath1281.93093OpenAlexW2051298848MaRDI QIDQ2436799

Ram Bilas Pachori, Pooja Jain

Publication date: 27 February 2014

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2013.01.002

zbMATH Keywords

signal to noise ratio (SNR)energy distribution of speech signalPseudo Wigner-Ville Distribution (PWVD) based methodvoiced/non-voiced (V/NV) detection

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10) Stochastic systems in control theory (general) (93E03)

Related Items (3)

Instantaneous voiced/non-voiced detection in speech signals based on variational mode decomposition ⋮ An iterative approach for decomposition of multi-component non-stationary signals based on eigenvalue decomposition of the Hankel matrix ⋮ Improved eigenvalue decomposition-based approach for reducing cross-terms in Wigner-Ville distribution

Uses Software

• WaveSurfer

Cites Work

• A comparison of the energy operator and the Hilbert transform approach to signal and speech demodulation
• Computing the discrete-time "analytic" signal via FFT
• A comparison of the existence of 'cross terms' in the Wigner distribution and the squared magnitude of the wavelet transform and the short-time Fourier transform
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