MATLAB-Based Implementation of a Spatial Covariance Matching Spread Rendering Method
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Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Modellbyggare
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Sammanfattning
A MATLAB implementation of the spatial covariance matching method proposed
by McCormack et al. is developed for the case of binaural reproduction and implemented
in an afSTFT framework using HRTFs, alongside baseline rendering (BL)
and eigenvalue decomposition (EVD) and optimal mixing (OM). In the OM method,
both prototype and residual mixing matrices are generated by the covariance-domain
optimization process as introduced in the original method. The evaluation of per
formance is done in terms of colouration, interaural level difference (ILD), interaural
coherence (IC), RMSE analysis over 836 source directions at different source spreads,
and signal distortion error (SDE). The results indicate that EVD improves coherence
matching and spatial diffuseness and OM yields a compromise between spatial
widening and signal preservation. The global performance is consistent overall with
the reference implementation, but differences exist between the implementations for
certain metrics and signal types in terms of quantity.
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Ämne/nyckelord
spatial covariance matching, source spread rendering, eigenvalue decom position, optimal mixing, afSTFT, HRTF, binaural rendering, interaural coherence, interaural level difference, signal distortion error
