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Table 3 Average STOI scores (%) comparisons of different noise states and basis vectors (\(\overline{J} = 40 ,{\overline{K}}= 25\))

From: A speech enhancement algorithm based on a non-negative hidden Markov model and Kullback-Leibler divergence

Parameters

\({\ddot{K}}=10\)

\({\ddot{K}}=20\)

\({\ddot{K}}=40\)

\({\ddot{K}}=70\)

Noisy

69.14 (\(\pm \,{0.51 }\))

NMF-HMM, \({\ddot{J}}=1\)

74.51 (\(\pm \,{0.51}\))

74.71 (\(\pm \, 0.51)\)

75.03 (\(\pm \,0.49\))

75.00 (\(\pm \, 0.48)\)

NMF-HMM, \({\ddot{J}}=2\)

75.00 (\(\pm \,{0.51 }\))

75.30 (\(\pm \, 0.50 )\)

75.51 (\(\pm \, 0.49\))

75.33 (\(\pm \, 0.47)\)

NMF-HMM, \({\ddot{J}}=5\)

75.44 (\(\pm \,{0.51 }\))

75.77 (\(\pm \, 0.50)\)

76.05 (\(\pm \, 0.47\))

75.15 (\(\pm \, 0.46)\)

NMF-HMM, \({\ddot{J}}=10\)

75.56 (\(\pm \,{0.50 }\))

76.11 (\(\pm \, 0.49)\)

76.27 (\(\pm \, 0.48\))

75.70 (\(\pm \, 0.46)\)