Add to ORKGKörner T, Geldreich S, Rückert U, Kasper K, Reininger H, Wüst H. Implementation of a Locally Recurrent Neural Network for Speech Recognition. In: Klar H, König A, Ramacher U, eds. Proceedings of the 6th International Conference on Microelectronics for Neural Networks, Evolutionary and Fuzzy Systems. Dresden, Germany; 1997: 50-55
This report introduces an hybrid speech recognition system for Speaker Independent (SI), continuous ...
This paper introduces Locally Recurrent Probabilistic Neural Networks (LRPNN) as an extension of the...
In this dissertation, we propose an accelerator for the implementation of Lthe ong Short-Term Memory...
The computational complexity of speech recognizers based on fully connected recurrent neural network...
Recurrent Neural Networks (RNN) provide a solution for low cost Speech Recognition Systems (SRS) in ...
This master thesis deals with the implementation of various types of recurrent neural networks via p...
SIGLEAvailable from British Library Document Supply Centre- DSC:D062610 / BLDSC - British Library Do...
. Here we report about investigations concerning the application of Fully Recurrent Neural Networks ...
Recurrent neural networks are an efficient tool for the solution of problems of automatic speech rec...
Abstract: This paper addresses the problem of speech recognition to identify various modes of speech...
This work introduces a multiple connectionist architecture based on a mixture of Recurrent Neural Ne...
Recently neural networks have been used successfully for real-time large vocabulary speech recogniti...
This paper presents a speech recognition sys-tem that directly transcribes audio data with text, wit...
This thesis addresses the problem of speech phone recognition. Phones are the acoustic sounds of spe...
This paper presents a speech recognition system which incorporates predictive neural networks. The ...
This report introduces an hybrid speech recognition system for Speaker Independent (SI), continuous ...
This paper introduces Locally Recurrent Probabilistic Neural Networks (LRPNN) as an extension of the...
In this dissertation, we propose an accelerator for the implementation of Lthe ong Short-Term Memory...
The computational complexity of speech recognizers based on fully connected recurrent neural network...
Recurrent Neural Networks (RNN) provide a solution for low cost Speech Recognition Systems (SRS) in ...
This master thesis deals with the implementation of various types of recurrent neural networks via p...
SIGLEAvailable from British Library Document Supply Centre- DSC:D062610 / BLDSC - British Library Do...
. Here we report about investigations concerning the application of Fully Recurrent Neural Networks ...
Recurrent neural networks are an efficient tool for the solution of problems of automatic speech rec...
Abstract: This paper addresses the problem of speech recognition to identify various modes of speech...
This work introduces a multiple connectionist architecture based on a mixture of Recurrent Neural Ne...
Recently neural networks have been used successfully for real-time large vocabulary speech recogniti...
This paper presents a speech recognition sys-tem that directly transcribes audio data with text, wit...
This thesis addresses the problem of speech phone recognition. Phones are the acoustic sounds of spe...
This paper presents a speech recognition system which incorporates predictive neural networks. The ...
This report introduces an hybrid speech recognition system for Speaker Independent (SI), continuous ...
This paper introduces Locally Recurrent Probabilistic Neural Networks (LRPNN) as an extension of the...
In this dissertation, we propose an accelerator for the implementation of Lthe ong Short-Term Memory...