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Stochastic models of glottal pulses from the Rosenberg and Liljencrants-Fant models with unified parameters., and . Comput. Speech Lang., (2021)Kernel concurrency opportunities based on GPU benchmarks characterization., , , , , , and . Clust. Comput., 23 (1): 177-188 (2020)Adapted Weighted Linear Prediction with Attenuated Main Excitation for formant frequency estimation in high-pitched singing., and . Speech Commun., (January 2024)A stochastic model of voice generation and the corresponding solution for the inverse problem using Artificial Neural Network for case with pathology in the vocal folds., and . Biomed. Signal Process. Control., (2021)Classification of Voice Aging Using Parameters Extracted from the Glottal Signal., , , and . ICANN (3), volume 6354 of Lecture Notes in Computer Science, page 149-156. Springer, (2010)Quantum-Inspired Features and Parameter Optimization of Spiking Neural Networks for a Case Study from Atmospheric., , , and . INNS Conference on Big Data, volume 53 of Procedia Computer Science, page 74-81. Elsevier, (2015)Jitter generation in voice signals produced by a two-mass stochastic mechanical model., and . Biomed. Signal Process. Control., (2016)Analysis and Characterization of GPU Benchmarks for Kernel Concurrency Efficiency., , , , , and . CARLA, volume 796 of Communications in Computer and Information Science, page 71-86. Springer, (2017)Evolutionary features and parameter optimization of spiking neural networks for unsupervised learning., , , and . IJCNN, page 2391-2398. IEEE, (2014)