• Corpus ID: 27194751

Convolutional neural networks for acoustic modeling of raw time signal in LVCSR

@inproceedings{Golik2015ConvolutionalNN,
  title={Convolutional neural networks for acoustic modeling of raw time signal in LVCSR},
  author={Pavel Golik and Zolt{\'a}n T{\"u}ske and Ralf Schl{\"u}ter and Hermann Ney},
  booktitle={INTERSPEECH},
  year={2015}
}
In this paper we continue to investigate how the deep neural network (DNN) based acoustic models for automatic speech recognition can be trained without hand-crafted feature extraction. [] Key Method This also allows us to interpret the weights of the second convolutional layer in the same way as 2D patches learned on critical band energies by typical convolutional neural networks. The evaluation is performed on an English LVCSR task. Trained on the raw time signal, the convolutional layers allow to reduce…

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