Heterogeneous Reservoir Computing Models for Persian Speech Recognition

Author:

Ansari Zohreh1,Pourhoseini Farzin1,Hadaeghi Fatemeh2

Affiliation:

1. Meybod University,Engineering Faculty,Biomedical Engineering Department,Meybod,Iran

2. Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf (UKE),Hamburg,Germany

Funder

Deutsche Forschungsgemeinschaft

Publisher

IEEE

Reference43 articles.

1. Optimization and applications of echo state networks with leaky- integrator neurons

2. Training and analysing deep recurrent neural networks;hermans;Advances in neural information processing systems,2013

3. Transfer Learning for End-to-End ASR to Deal with Low-Resource Problem in Persian Language

4. An end-to-end deep learning model to recognize Farsi speech from raw input

5. Improving phoneme sequence recognition using phoneme duration information in DNN-HSMM;asadolahzade kermanshahi;Journal of AI and Data Mining,2019

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2. DI-ESN: Dual Input-Echo State Network for Time Series Forecasting;2023 International Symposium on Networks, Computers and Communications (ISNCC);2023-10-23

3. Real-Time Photonic Deep Reservoir Computing for Speech Recognition;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

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