Boltzmann machines for speech recognition
Computer Speech and Language
Dynamics and architecture for neural computation
Journal of Complexity - Special Issue on Neural Computation
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
A continuous speech recognition system embedding MLP into HMM
Advances in neural information processing systems 2
Generalization and parameter estimation in feedforward nets: some experiments
Advances in neural information processing systems 2
The acoustic-modeling problem in automatic speech recognition
The acoustic-modeling problem in automatic speech recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Off-Line Handwritten Word Recognition Using a Hidden Markov Model Type Stochastic Network
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Contextual Information to Selectively Adjust Preprocessing Parameters
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
Context Dependent Phoneme Recognition
TSD '99 Proceedings of the Second International Workshop on Text, Speech and Dialogue
A tutorial on text-independent speaker verification
EURASIP Journal on Applied Signal Processing
Parallel distributed belief networks that learn
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Context-dependent hidden control neutral network architecture for continuous speech recognition
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Digital Signal Processing
A time-frequency segmental neural network for phoneme recognition
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Using parallel MLPs as labelers for multiple codebook HMMs
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Speech recognition using dynamical model of speech production
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Speech recognition using stereo vision neural networks with competition and cooperation
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
International Journal of Speech Technology
Neural net pattern recognition equations with self-organization for phoneme recognition
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Tandem connectionist feature extraction for conversational speech recognition
MLMI'04 Proceedings of the First international conference on Machine Learning for Multimodal Interaction
Artificial Intelligence in Medicine
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The statistical use of a particular classic form of a connectionist system, the multilayer perceptron (MLP), is described in the context of the recognition of continuous speech. A discriminant hidden Markov model (HMM) is defined, and it is shown how a particular MLP with contextual and extra feedback input units can be considered as a general form of such a Markov model. A link between these discriminant HMMs, trained along the Viterbi algorithm, and any other approach based on least mean square minimization of an error function (LMSE) is established. It is shown theoretically and experimentally that the outputs of the MLP (when trained along the LMSE or the entropy criterion) approximate the probability distribution over output classes conditioned on the input, i.e. the maximum a posteriori probabilities. Results of a series of speech recognition experiments are reported. The possibility of embedding MLP into HMM is described. Relations with other recurrent networks are also explained.