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Given the use of different stimuli in the close and distant conditions, also other possible confounding variables (visual complexity and familiarity) were taken into account and carefully controlled (see Supplementary material for further details).
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In the "Distant" condition, the source traveled between 15 m and 60 m from the median plane of the listener.
Flow features represented in the model include an impermeable arc-shaped barrier wall and multiple wells; distant boundary conditions are not included explicitly, but their effects on the local flow field are modelled by specifying a uniform flow at infinity and a constant areal recharge within a local domain.
The model for the calculation of an equivalent static force (ESF) and the design procedure with ESF for single-degree-of-freedom (SDOF) systems presented in the first part of the two-part paper are extended into the design for a reinforced concrete (RC) frame structure under distant blast conditions.
Table 5 lists the performance comparisons on RealData for distant-talking conditions with multi-channel front-end.
The speaker recognition rates based on CMN for distant-talking conditions are very low because late reverberation cannot be suppressed.
Table 4 gives a performance comparison of different single-channel systems on RealData for distant-talking conditions.
DNN-JT2 was better than DNN-JT1 for distant-talking conditions, which was opposite for close-talking conditions in Table 3.
Furthermore, the jointly trained DNNs are much more robust to real-world testing speech than multi-condition training DNNs for both close-talking and distant-talking conditions.
This might be due to that there was a strong complementarity between the original and processed features in distant-talking conditions.
First, Multi-2 achieved a relative WER reduction of 7.3 % in average over Multi-1 in the distant-talking conditions, which was more significant than that in close-talking conditions.
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CEO of Professional Science Editing for Scientists @ prosciediting.com