Voicenet is an open source speech synthesis framework based on tensorflow and sonnet. This flexible architecture lets you validate your new neural network based acoustic model quickly in your experiments, and owing to the deployment capability of tensorflow, we think it's easy to deploy new algorithms and experiments online for serving.
We have simplify the dependencies of voicenet, so you will need to install tensorflow>=v1.7.0 and progress only.
pip install -r requirements.txt- Clone this repository with
git clone https://github.com/npuichigo/voicenet.git - Go to
voicenet/toolsand run the scriptcompile_tools.shto compile third_party tools - Go to
voicenet/egs/slt_arctic/and run the scriptrun.sh - For your own dataset, just make a new directory under
voicenet/egs/, copyvoicenet/egs/localandvoicenet/egs/run.shto the new workspace
WARNING:You should change the training parameters for your own dataset. For the purpose of demostration, batch_size is set to one in voicenet/egs/slt_arctic/.
IMPORTANT:We remove the dependency of sonnet in the latest version of voicenet. The main reason is that we want to keep track of tensorflow's rapid updates. In addition, starting in tensorflow 1.2, dataset iterator is added for reading data into tensorflow. In using tensorflow's dataset api, iterators of dataset_train and dataset_valid can be merged into one iterator, which can be switched between different datasets conveniently, so variable reuse is no longer needed.
model = LSTM(...)
iterator = tf.contrib.data.Iterator.from_structure(
dataset_train.batched_dataset.output_types,
dataset_train.batched_dataset.output_shapes)
input, _ = iterator.get_next()
output = model(input)