Employing Robust Principal Component Analysis for Noise-Robust Speech Feature Extraction in Automatic Speech Recognition with the Structure of a Deep Neural Network
Hung, J.-w.; Lin, J.-S.; Wu, P.-J. Employing Robust Principal Component Analysis for Noise-Robust Speech Feature Extraction in Automatic Speech Recognition with the Structure of a Deep Neural Network. Appl. Syst. Innov. 2018, 1, 28. https://doi.org/10.3390/asi1030028
Hung J-w, Lin J-S, Wu P-J. Employing Robust Principal Component Analysis for Noise-Robust Speech Feature Extraction in Automatic Speech Recognition with the Structure of a Deep Neural Network. Applied System Innovation. 2018; 1(3):28. https://doi.org/10.3390/asi1030028
Chicago/Turabian StyleHung, Jeih-weih, Jung-Shan Lin, and Po-Jen Wu. 2018. "Employing Robust Principal Component Analysis for Noise-Robust Speech Feature Extraction in Automatic Speech Recognition with the Structure of a Deep Neural Network" Applied System Innovation 1, no. 3: 28. https://doi.org/10.3390/asi1030028