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EURASIP Journal on Audio, Speech, and Music Processing

Table 1 The expensive operations in the different methods for Gaussian-based MLE imputation with full covariance matrices

From: Multi-candidate missing data imputation for robust speech recognition

 

Full precision matrix in cache

Number of iterations

Likelihood #multiplications

Step calculation #multiplications

Other

MAP [24]

Yes

6

(D + 1)D

(D t, u + 1)D t, u

No

MU [32]

Yes

5

(D + 1)D

D t, u D t, u + 4D t, u

D t, u √ per step

GD + cepstral

No

2

2D m D + D m + D

D t, u (2D m + 3) + D m D + D m + D

No

GD + PROSPECT

No

2

2(D c + D)

3D c D t, u + 4D c D + 5D + 3D c

No

  1. D is the dimension of the log spectral features. D m is the order of the cepstral coefficients in MFCC. D t, u is the number of unreliable components at frame t. D c is the order of the cepstra in PROSPECT features. Typical values: D = 22, D m = 13, D c = 4. D t, u is about 16 on average as measured in [33].
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