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generalized cross-correlation.
An eigenstructure-based generalized cross-correlation method is proposed to estimate time delay among microphones.
The improved version of the CC method is the generalized cross-correlation (GCC) method [13].
Using generalized cross-correlation techniques both upward and downward velocities are found.
The generalized cross-correlation technique is used to detect the source positions.
For larger spacing, a variant of the generalized cross-correlation with phase transform (GCC-PHAT) method performs best.
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TDE functions include the generalized cross correlation (GCC) [19] which is defined for a frame of microphone pair data: (6).
The generalized cross correlation (GCC) method is the most important approach for estimating TDOA between microphone pairs.
GCC-PHAT (Generalized Cross Correlation-PHAse Transform) Patterns, computed from the audio signals captured by the microphone are used as input features for the DNN.
A very popular TDOA estimation approach is the generalized cross correlation (GCC) method [23, 28, 29], where the cross-correlation between the microphone signals is calculated in the frequency domain as the cross power spectral density (CPSD).
To estimate the delays τ l,j (k) in samples between the microphones and thereby the direction of the beamformer, a generalized cross correlation (GCC) function is utilized as presented in [26].
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