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We present a state-of-the-art speech recognition system developed using end-to-end deep learning. Our architecture is… Expand Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training methods such as Connectionist… Expand We describe the design of Kaldi, a free, open-source toolkit for speech recognition research. Kaldi provides a speech recognition… Expand We survey the use of weighted finite-state transducers (WFSTs) in speech recognition. We show that WFSTs provide a common and… Expand From the Publisher:
This book takes an empirical approach to language processing, based on applying statistical and other… Expand Abstract This paper examines the application of linear transformations for speaker and environmental adaptation in an HMM-based… Expand The speech recognition problem hidden Markov models the acoustic model basic language modelling the Viterbi search hypothesis… Expand 1. Fundamentals of Speech Recognition. 2. The Speech Signal: Production, Perception, and Acoustic-Phonetic Characterization. 3… Expand From the Publisher:
Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to… Expand The use of hidden Markov models for speech recognition has become predominant in the last several years, as evidenced by the… Expand