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+,"&6E%&2* <H!!"#$%&'()"&*+",*,%-%,.%,()"&J** N(6C4&'Z*'4,E'),*$(,(24L#* >H! V"2%554&L*'4,E'),* [H! A%&%,(54'4&L*6"*&(61,(54')3*'$%%30* YH! U%-%,.%,()"&*,".1'6*+,"&6E%&2*+",*8RU* [=*"+*Y=*

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,%-%,.%,()"&*,".1'6*+,"&6E%&2* $(,(55%5E54C%540""2*#"2%5* &"+,&"-../ 01.2'$,%1' 2./,&'!7"7#89! $ 8'!"#$%&' ()**' /,3,43' 1,5,16' 4.$/"3".$!' &"+,&"-../' :,"#-3"$#' (>?'.0,$5,&.;, &"+,&"-../ 01.2'0%1' 2./,&'!7"7#89! 0 8' ;-.$,'!,<=,$4,' /,4./,' Y[* "+*Y=*

,%-%,.%,()"&*,".1'6*+,"&6E%&2* $(,(55%5E54C%540""2*#"2%5* Human near-near Oracle model near-near MPR model near-near SIR SKUR SPUR STIR SIR SKUR SPUR STIR φ 2 SIR SKUR SPUR STIR φ 2 SIR 37 0 0 3 SIR 32 0 0 8 0.0329 SIR 32 0 0 8 0.0329 SKUR 0 40 0 0 SKUR 0 38 0 2 0.0256 SKUR 0 38 0 2 0.0256 SPUR 0 1 38 1 SPUR 2 0 38 0 0.0500 SPUR 2 0 34 4 0.0628 STIR 0 0 0 40 STIR 0 2 0 38 0.0256 STIR 2 2 2 34 0.0811 Human near-far Oracle model near-far MPR model near-far SIR SKUR SPUR STIR SIR SKUR SPUR STIR φ 2 SIR SKUR SPUR STIR φ 2 SIR 37 0 0 3 SIR 36 2 2 0 0.0877 SIR 36 0 2 2 0.0277 SKUR 6 29 2 3 SKUR 6 34 0 0 0.0675 SKUR 6 34 0 0 0.0675 SPUR 16 3 19 2 SPUR 6 2 30 2 0.0902 SPUR 10 2 28 0 0.0664 STIR 16 2 1 21 STIR 18 6 0 16 0.0474 STIR 16 6 0 18 0.0404 Human far-far Oracle model far-far MPR model far-far SIR SKUR SPUR STIR SIR SKUR SPUR STIR φ 2 SIR SKUR SPUR STIR φ 2 SIR 33 1 1 5 SIR 22 4 4 10 0.0933 SIR 28 2 4 6 0.0329 SKUR 0 34 0 6 SKUR 2 36 0 2 0.0507 SKUR 4 32 0 4 0.0558 SPUR 3 2 31 4 SPUR 4 0 36 0 0.0814 SPUR 6 0 32 2 0.0460 STIR 2 1 0 37 STIR 0 0 0 40 0.0390 STIR 0 0 0 40 0.0390 Table 1: Confusion matrices for human listeners (left), computer model given oracle information about the reverberation condition (center) and computer model that uses a MPR metric to determine the reverberation condition (right). Reverberation conditions are labelled as context-test distance. Rows correspond to the stimuli presented; columns record the responses. YY* "+*Y=*

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