Shi Y., Larson M., Pelemans J., Jonker C.M., Wambacq P., Wiggers P., Demuynck K., ''Integrating meta-information into recurrent neural network language models'', Speech communication, vol. 73, pp. 64-80, October 2015.status: publishe
Language modeling is a crucial component in a wide range of applications including speech recognitio...
This repository contains the raw results (by word information-theoretic measures for the experimenta...
The files in the dataset correspond to results that have been generated for the IEEE/ACM Transaction...
Verwimp L., Pelemans J., Van hamme H., Wambacq P., ''Augmenting recurrent neural network language mo...
© 2015 Elsevier B.V. All rights reserved. Due to their advantages over conventional n-gram language ...
Recurrent neural network language models (RNNLMs) are powerful language modeling techniques. Signifi...
de Raedt L, Hammer B, Hitzler P, Maass W, eds. Recurrent Neural Networks - Models, Capacities, and A...
The task of part-of-speech (POS) language modeling typically includes a very small vocabulary, which...
In this paper we present a survey on the application of recurrent neural networks to the task of sta...
Comunicació presentada a la 2016 Conference of the North American Chapter of the Association for Com...
National Research Foundation (NRF) Singapore under AI Singapore Programme; Lee Kong Chian Fellowshi
<p>RNN models trained on MS-COCO used in the following paper:</p> <p>Ákos Kádár, Grzegorz Chrupała,...
During recent years, neural networks show crucial improvement in catching semantics of words or sen...
The seminar centered around recurrent information processing in neural systems and its connections t...
The recurrent neural network language model (RNNLM) has been demonstrated to consistently reduce per...
Language modeling is a crucial component in a wide range of applications including speech recognitio...
This repository contains the raw results (by word information-theoretic measures for the experimenta...
The files in the dataset correspond to results that have been generated for the IEEE/ACM Transaction...
Verwimp L., Pelemans J., Van hamme H., Wambacq P., ''Augmenting recurrent neural network language mo...
© 2015 Elsevier B.V. All rights reserved. Due to their advantages over conventional n-gram language ...
Recurrent neural network language models (RNNLMs) are powerful language modeling techniques. Signifi...
de Raedt L, Hammer B, Hitzler P, Maass W, eds. Recurrent Neural Networks - Models, Capacities, and A...
The task of part-of-speech (POS) language modeling typically includes a very small vocabulary, which...
In this paper we present a survey on the application of recurrent neural networks to the task of sta...
Comunicació presentada a la 2016 Conference of the North American Chapter of the Association for Com...
National Research Foundation (NRF) Singapore under AI Singapore Programme; Lee Kong Chian Fellowshi
<p>RNN models trained on MS-COCO used in the following paper:</p> <p>Ákos Kádár, Grzegorz Chrupała,...
During recent years, neural networks show crucial improvement in catching semantics of words or sen...
The seminar centered around recurrent information processing in neural systems and its connections t...
The recurrent neural network language model (RNNLM) has been demonstrated to consistently reduce per...
Language modeling is a crucial component in a wide range of applications including speech recognitio...
This repository contains the raw results (by word information-theoretic measures for the experimenta...
The files in the dataset correspond to results that have been generated for the IEEE/ACM Transaction...