  The Kaldi toolkit is becoming popular for constructing automated speech
recognition (ASR) systems. Meanwhile, in recent years, deep neural networks
(DNNs) have shown state-of-the-art performance on various ASR tasks. This
document describes our open-source recipes to implement fully-fledged DNN
acoustic modeling using Kaldi and PDNN. PDNN is a lightweight deep learning
toolkit developed under the Theano environment. Using these recipes, we can
build up multiple systems including DNN hybrid systems, convolutional neural
network (CNN) systems and bottleneck feature systems. These recipes are
directly based on the Kaldi Switchboard 110-hour setup. However, adapting them
to new datasets is easy to achieve.
