Speech quality evaluation of artificial bandwidth extension: comparing subjective judgments and instrumental predictions

2015 ◽  
Author(s):  
Hannu Pulakka ◽  
Ville Myllylä ◽  
Anssi Rämö ◽  
Paavo Alku
Keyword(s):  
Quality Evaluation ◽  
Speech Quality ◽  
Bandwidth Extension ◽  
Subjective Judgments ◽  
Artificial Bandwidth Extension

Conversational quality evaluation of artificial bandwidth extension of telephone speech

2012 ◽  
Vol 132 (2) ◽  
pp. 848-861 ◽  
Author(s):  
Hannu Pulakka ◽  
Laura Laaksonen ◽  
Santeri Yrttiaho ◽  
Ville Myllylä ◽  
Paavo Alku
Keyword(s):  
Quality Evaluation ◽  
Bandwidth Extension ◽  
Telephone Speech ◽  
Artificial Bandwidth Extension

scholarly journals Speech quality prediction for artificial bandwidth extension algorithms

2013 ◽  
Author(s):  
Sebastian Möller ◽  
Emilia Kelaidi ◽  
Friedemann Köster ◽  
Nicolas Côté ◽  
Patrick Bauer ◽  
...  
Keyword(s):  
Speech Quality ◽  
Quality Prediction ◽  
Bandwidth Extension ◽  
Extension Algorithms ◽  
Artificial Bandwidth Extension

A Novel Recurrent Generalized Congruence Neural Network Measure for Objective Speech Quality Evaluation

2012 ◽  
Vol 433-440 ◽  
pp. 2282-2287
Author(s):  
Tian Yun Yan
Keyword(s):  
Neural Network ◽  
Quality Evaluation ◽  
Speech Quality ◽  
System Model ◽  
The Novel ◽  
Training Time ◽  
Network Measure ◽  
Comparison Results ◽  
Objective Speech Quality ◽  
New System

A new system model for objective speech quality evaluation based on the improved recurrent generalized congruence neural network (RGCNN/OSQE) is proposed. The performance of the RGCNN model is compared with the most commonly used RBFNN (radial basis function neural network) model in objective speech quality evaluation. Comparison results show that the RGCNN model has higher correlation coefficient, less deviation, and saves about half training time, i.e., the RGCNN model has obvious advantages over the RBFNN model. Therefore, the novel RGCNN model for objective speech quality evaluation is feasible and effective.

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