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Bidirectional recurrent neural networks

Bidirectional Recurrent Neural Networks(BRNN) were invented in 1997 by Schuster & Paliwal. BRNN is introduced to increase the amount of input… 
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Related topics

Related topics

5 relations
Artificial neural networkLong short-term memoryMultilayer perceptronRecurrent neural network

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Confidence Estimation and Deletion Prediction Using Bidirectional Recurrent Neural Networks
The standard approach to assess reliability of automatic speech transcriptions is through the use of confidence scores. If… 
2018
2018
Bigrams and BiLSTMs Two Neural Networks for Sequential Metaphor Detection
We present and compare two alternative deep neural architectures to perform word-level metaphor detection on text: a bi-LSTM… 
2018
2018
Cyclist Trajectory Prediction Using Bidirectional Recurrent Neural Networks
Predicting a long-term horizon of vulnerable road users’ trajectories such as cyclists become an inevitable task for a reliable… 
Highly Cited
2017
Highly Cited
2017
Error detection and accuracy estimation in automatic speech recognition using deep bidirectional recurrent neural networks
2016
2016
Sentiment classification using Comprehensive Attention Recurrent models
Sentiment classification has been a very hot topic in the field of natural language processing (NLP) and understanding in recent… 
2016
2016
Video Description Using Bidirectional Recurrent Neural Networks
Although traditionally used in the machine translation field, the encoder-decoder framework has been recently applied for the… 
Highly Cited
2015
Highly Cited
2015
Artificial Neural Networks Applied to Taxi Destination Prediction
We describe our first-place solution to the ECML/PKDD discovery challenge on taxi destination prediction. The task consisted in… 
2015
2015
Chinese Semantic Role Labeling with Bidirectional Recurrent Neural Networks
Traditional approaches to Chinese Semantic Role Labeling (SRL) almost heavily rely on feature engineering. Even worse, the long… 
2015
2015
ASR error detection and recognition rate estimation using deep bidirectional recurrent neural networks
Recurrent neural networks (RNNs) have recently been applied as the classifiers for sequential labeling problems. In this paper… 
Highly Cited
2014
Highly Cited
2014
Feature enhancement by deep LSTM networks for ASR in reverberant multisource environments
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