Multi-resolution speech analysis for automatic speech recognition using deep neural networks: Experiments on TIMIT
Table 5
Results with multi-resolution spectrograms and TDNNs-ReLU networks with ±10 feature splicing.
In all cases features are raw spectrograms in dB obtained with Hamming windows. Input Dim. is the dimension of the input of the network including feature splicing. Param. is the number of trainable parameters of the network.