Improved Silence-Unvoiced-Voiced (SUV) Segmentation for Dysarthric Speech Signals using Linear Prediction Error Variance

2020 ◽  
Author(s):  
Tolulope Ijitona ◽  
Hong Yue ◽  
John Soraghan ◽  
Anja Lowit
Keyword(s):  
Prediction Error ◽  
Linear Prediction ◽  
Error Variance ◽  
Speech Signals ◽  
Prediction Error Variance ◽  
Dysarthric Speech

Prediction of Upper-Air Winds over Cape Canaveral1

1961 ◽  
Vol 42 (8) ◽  
pp. 522-526 ◽  
Author(s):  
C. T. Striebel ◽  
R. E. Bieber
Keyword(s):  
Linear Regression ◽  
Prediction Error ◽  
Linear Prediction ◽  
Winter Season ◽  
Error Variance ◽  
Jet Stream ◽  
Regression Methods ◽  
Prediction Error Variance ◽  
Wind Measurements ◽  
Altitude Level

The prediction-error variance has been obtained by linear-regression methods for various 12-hr and 24-hr predictions of winter-season winds over Cape Canaveral, Florida. The prediction schemes employed include the most sophisticated which utilizes all of the wind measurements at all of the altitude levels as well as the simplest which utilizes only the measurements at the same altitude level. The results show that very little is gained by considering the most sophisticated or “Best Linear Prediction” as opposed to the simplest. Also, very little is gained by taking more than one sounding in advance of the prediction. An appreciable decrease in the error variance, especially in the region just below the jet-stream altitude, is realized for the 12-hr as compared to the 24-hr prediction.

scholarly journals Asymptotic Prediction Error Variance for Feedforward Neural Networks

2020 ◽  
Vol 53 (2) ◽  
pp. 1108-1113
Author(s):  
Magnus Malmström ◽  
Isaac Skog ◽  
Daniel Axehill ◽  
Fredrik Gustafsson
Keyword(s):  
Neural Networks ◽  
Prediction Error ◽  
Feedforward Neural Networks ◽  
Error Variance ◽  
Prediction Error Variance
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