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Improved TDNNs using Deep Kernels and Frequency Dependent Grid-RNNs
Time delay neural networks (TDNNs) are an effective acoustic model for large vocabulary speech recognition.
High Order Recurrent Neural Networks for Acoustic Modelling
Vanishing long-term gradients are a major issue in training standard recurrent neural networks (RNNs), which can be alleviated by long short-term memory (LSTM) models with memory cells.
Semi-tied Units for Efficient Gating in LSTM and Highway Networks
Gating is a key technique used for integrating information from multiple sources by long short-term memory (LSTM) models and has recently also been applied to other models such as the highway network.
Multi-Span Acoustic Modelling using Raw Waveform Signals
This paper proposes a novel multi-span structure for acoustic modelling based on the raw waveform with multiple streams of CNN input layers, each processing a different span of the raw waveform signal.
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