Integrating Deep Neural Networks into Structural Classification Approach based on Weighted Finite-State Transducers

17 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep Learning: Methods and Applications (2014, background): “The collaboration continued to large vocabulary tasks with more convincing, highly positive results [67, 68, 94, 89, 161, 199, 195, 223, 323, 353, 399, 414].”
A tutorial survey of architectures, algorithms, and applications for deep learning (2014, background): “, 2013) and large vocabulary speech recognition tasks (Yu et al., 2012; Seide et al., 2011; Dahl et al., 2011, 2012; Kubo et al., 2012; Deng et al, 2013b, 2013c; Yan et al., 2013) by integrating the powerful discriminative training ability of DNNs with the sequential modeling ability of HMMs.”
Listen, attend and spell: A neural network for large vocabulary conversational speech recognition (2015, methodology): “In these models, acoustic models are updated based on a WER proxy, while the pronunciation and language models are rarely updated [7], if at all.”