Large Vocabulary Speech Recognition Using Deep Tensor Neural Networks

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Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank (2013, methodology): “, 2012), extending Restricted Boltzmann machines (Ranzato and Hinton, 2010) and as a special layer for speech recognition (Yu et al., 2012).”
Deep Learning: Methods and Applications (2014, background): “[421, 422], which extends the conventional DNN by replacing one or more of its layers with a double-projection layer and a tensor layer.”
The Deep Tensor Neural Network With Applications to Large Vocabulary Speech Recognition (2013, result): “This work significantly extends and completes the preliminary work described in [1].”
Recursive deep learning for natural language processing and computer vision (2014, background): “, 2012), extending Restricted Boltzmann machines (Ranzato and Hinton, 2010) and as a special layer for speech recognition (Yu et al., 2012).”
On the Expressive Power of Deep Learning: A Tensor Analysis (2015, unknown): “Socher et al. (2013), Yu et al. (2012), Setiawan et al. (2015), and Hutchinson et al. (2013) all proposed different neural network architectures that include tensor-based elements, and exhibit various advantages in terms of expressiveness and/or ease of training.”
Reasoning With Neural Tensor Networks for Knowledge Base Completion (2013, background): “[13] introduce a model with tensor layers for speech recognition.”