Non-intrusive Intelligibility Prediction of Noise-suppressed Speech Based on Neural Network
Author:
Affiliation:
1. Southern University of Science and Technology,Shenzhen Key Laboratory of Robotics Perception and Intelligence,Shenzhen,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9880547/9880568/09880587.pdf?arnumber=9880587
Reference20 articles.
1. Predicting the intelligibility of noise-corrupted speech non-intrusively by across-band envelope correlation
2. Assessing the segmental contribution to the non-intrusive intelligibility prediction of noise-suppressed speech
3. Speech quality objective assessment using neural network;fu;Acoustics Speech and Signal Processing (ICASSP) International Conference On IEEE,0
4. Non-intrusive quality assessment for enhanced speech signals based on spectro-temporal features;li;IEEE International Conference on Multimedia and Expo Workshops (ICMEW),2014
5. Sound quality prediction of vehicle interior noise and mathematical modeling using a back propagation neural network (BPNN) based on particle swarm optimization (PSO)
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