Influence of informational content of background noise on speech quality evaluation for VoIP application

2008 ◽  
Vol 123 (5) ◽  
pp. 3066-3066 ◽  
Author(s):  
Adrien Leman ◽  
Julien Faure ◽  
Etienne Parizet
Keyword(s):  
Background Noise ◽  
Quality Evaluation ◽  
Speech Quality ◽  
Informational Content

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.

Speech quality evaluation for different pitch detection algorithms in LPC speech analysis–synthesis system

2020 ◽  
Author(s):  
Sandeep Kumar ◽  
Sneha Singh ◽  
Prabhakar Agarwal ◽  
Upendra Kumar Acharya ◽  
Prabira Kumar Sethy ◽  
...  
Keyword(s):  
Quality Evaluation ◽  
Speech Quality ◽  
Speech Analysis ◽  
Pitch Detection ◽  
Synthesis System ◽  
Detection Algorithms

TESPAR coded speech quality evaluation (TCSQE)

AFRICON 2009 ◽  
2009 ◽  
Author(s):  
Philip O. Adar ◽  
Marcel O. Odhiambo
Keyword(s):  
Quality Evaluation ◽  
Speech Quality
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