Applied Speech and Audio Processing: With matlab examples
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Applied Speech and Audio Processing With MATLAB Examples ( PDFDrive )
Audio analysis
As such it is quite easily described as an integral across analysis window w in Equation (6.9). S x (t, v) = x (u)w(u − t)e −j2πvu du 2 . (6.9) The instantaneous frequency energy at time t is then given by: E x (t) = 1 2 S x (t, v)dv. (6.10) The Wigner–Ville distribution (WVD) is a bilinear distribution that is qualitatively dif- ferent from the STFD. At any particular time, the signal contributions from the past are multiplied by the signal contributions from the future in order to compute and correlate between these left and right parts of the signal. It has the ability to give a clearer picture of the instantaneous frequency and group delay than the spectrogram: WV x (t, v) = x t + τ 2 x t − τ 2 e −j2πvτ d τ. (6.11) Similarly, the instantaneous frequency energy at time t is then given by: E x (t) = 1 2 |WV x (t, v)| dv. (6.12) Although the WVD is perfectly localised on linear signals due to the forward-backward nature of the analysis. However, if there are several frequency components existing simultaneously, noise will be found in the WVD distribution due to the phenomenon of cross-term interference between those components. It also provides equal weighting to both past and future components. The pseudo-Wigner–Ville distribution (PWVD) is an advance on the WVD since it emphasises the signal properties near the time of interest compared to far away times. A window function h (τ) is used that peaks around τ = 0 to weight the Wigner–Ville distribution toward an emphasis of the signal around time t. The PWVD is defined as: PWV x (t, v) = h (τ)x t + τ 2 x t − τ 2 e −j2πvτ d τ. (6.13) Again, the instantaneous frequency energy calculation at time t is relatively simple: E x (t) = 1 2 |PWV x (t, v)| dv. (6.14) Finally, a fourth method exists as a refinement to PWVD. This is the reassigned smoothed PWVD (refer to [8] for its application). It uses a centre-of-gravity reassignment method with both time and frequency domain smoothing. |
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