Bangla Speaker Accent Variation Detection by MFCC Using Recurrent Neural Network Algorithm: A Distinct Approach

2020 ◽  
pp. 545-553
Author(s):  
Rezaul Karim Mamun ◽  
Sheikh Abujar ◽  
Rakibul Islam ◽  
Khalid Been Md. Badruzzaman ◽  
Mehedi Hasan
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Distinct Approach

A STUDY OF TRACK FINDING WITH A NEURAL NETWORK ALGORITHM

1992 ◽  
Vol 03 (supp01) ◽  
pp. 303-308
Author(s):  
Giuseppe Barbagli ◽  
Guido Castellini ◽  
Gregorio Landi ◽  
Stefano Vettori
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Hardware Implementation ◽  
Initial Conditions ◽  
Hopfield Model ◽  
Network Algorithm ◽  
Random Initial Conditions ◽  
Neural Network Algorithm

We have investigated the problem of track finding with a recurrent neural network algorithm based on the Hopfield model and considered the possibility of a hardware implementation with DSP’s. Starting from a set of signal points we define track segments and set a cut on the length to keep the size of the network reasonable. Those segments surviving the cut are associated to neurons. A geometric coupling of neighbouring segments is used to select smooth combinations of them. Given random initial conditions the network converges to a solution. The method may be applied to a variety of curves.

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