Bidirectional Dynamics for Protein Secondary Structure Prediction
Sequence Learning - Paradigms, Algorithms, and Applications
Learning precise timing with lstm recurrent networks
The Journal of Machine Learning Research
Neural Computation
Bidirectional recurrent neural networks
IEEE Transactions on Signal Processing
An application of recurrent nets to phone probability estimation
IEEE Transactions on Neural Networks
ICML '06 Proceedings of the 23rd international conference on Machine learning
Training Recurrent Networks by Evolino
Neural Computation
Atrial fibrillation classification with artificial neural networks
Pattern Recognition
Anticipations, Brains, Individual and Social Behavior: An Introduction to Anticipatory Systems
Anticipatory Behavior in Adaptive Learning Systems
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Sequence labelling in structured domains with hierarchical recurrent neural networks
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Handwriting Recognition Algorithm in Different Languages: Survey
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
Multi-dimensional recurrent neural networks
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
An application of recurrent neural networks to discriminative keyword spotting
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
3d gesture recognition applying long short-term memory and contextual knowledge in a CAVE
Proceedings of the 1st ACM international workshop on Multimodal pervasive video analysis
Emotion on the road: necessity, acceptance, and feasibility of affective computing in the car
Advances in Human-Computer Interaction - Special issue on emotion-aware natural interaction
An unsupervised learning based LSTM model: a new architecture
AMERICAN-MATH'11/CEA'11 Proceedings of the 2011 American conference on applied mathematics and the 5th WSEAS international conference on Computer engineering and applications
Bidirectional LSTM networks for improved phoneme classification and recognition
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Tandem decoding of children's speech for keyword detection in a child-robot interaction scenario
ACM Transactions on Speech and Language Processing (TSLP)
Enhancing spontaneous speech recognition with BLSTM features
NOLISP'11 Proceedings of the 5th international conference on Advances in nonlinear speech processing
A multitask approach to continuous five-dimensional affect sensing in natural speech
ACM Transactions on Interactive Intelligent Systems (TiiS) - Special Issue on Affective Interaction in Natural Environments
Recognizing connected digit strings using neural networks
TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue
Recurrent sparse support vector regression machines trained by active learning in the time-domain
Expert Systems with Applications: An International Journal
Dominance detection in a reverberated acoustic scenario
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Keyword spotting exploiting Long Short-Term Memory
Speech Communication
Learning sequence neighbourhood metrics
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Computer Speech and Language
LSTM-Modeling of continuous emotions in an audiovisual affect recognition framework
Image and Vision Computing
Engineering Applications of Artificial Intelligence
Recent developments in openSMILE, the munich open-source multimedia feature extractor
Proceedings of the 21st ACM international conference on Multimedia
| Hi-index | 0.00 |
In this paper, we present bidirectional Long Short Term Memory (LSTM) networks, and a modified, full gradient version of the LSTM learning algorithm. We evaluate Bidirectional LSTM (BLSTM) and several other network architectures on the benchmark task of framewise phoneme classification, using the TIMIT database. Our main findings are that bidirectional networks outperform unidirectional ones, and Long Short Term Memory (LSTM) is much faster and also more accurate than both standard Recurrent Neural Nets (RNNs) and time-windowed Multilayer Perceptrons (MLPs). Our results support the view that contextual information is crucial to speech processing, and suggest that BLSTM is an effective architecture with which to exploit it.