Welcome to the world of Neural Network (NN) based speech synthesis! In this guide, we will walk you through the installation and utilization of Merlin, a remarkable toolkit developed at the Centre for Speech Technology Research (CSTR) at the University of Edinburgh. With its ability to turn text into lifelike speech, Merlin harnesses the power of deep learning in a way that opens up a plethora of opportunities for developers and researchers alike.

Installation of Merlin

Before you dive into using Merlin, you’ll need to set it up on your machine. Follow these steps to ensure a smooth installation process:

• Ensure that you have Python installed (compatible versions: 2.7-3.6).
• Install Dependencies:
  • numpy
  • scipy
  • matplotlib
  • bandmat
  • theano
  • tensorflow (optional, but necessary for TensorFlow models)
  • sklearn, keras, h5py (optional for Keras models)
• Navigate to the Merlin directory and run the following commands:

bash tools/compile_tools.sh
pip install -r requirements.txt

Getting Started with Merlin

Once you’ve got Merlin set up, it’s time to explore its capabilities. To get your first taste of the system, check out the example builds:

• For a simple demo, follow the scripts in the egs/slt_arctic directory.
• You can also refer to Josh Meyers’ blog post for detailed guidance on installing Merlin and building the SLT demo voice.

Deep Dive into Building Voices

If you wish to hone your skills further and build custom voices, consider the following resources:

• Deep Learning for Text-to-Speech Synthesis, using the Merlin toolkit (Interspeech 2017 tutorial)
• Arctic voices
• Build your own voice

Synthetic Speech Samples

Don’t just read about it; listen to the magic of synthetic speech! Check out the available synthetic speech samples showcasing the SLT Arctic voice. It’s a great way to gauge the quality and capabilities of the system.

Troubleshooting and Community Support

If you encounter any issues during installation or usage, here are some troubleshooting tips:

• Make sure all dependencies are correctly installed and compatible with your version of Python.
• Consult the INSTALL documentation for specific guidelines on your operating system.
• If problems persist, consider posting your queries on the GitHub Issues page.

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Development Path for Contributors

If you’re interested in contributing to Merlin, here’s a simple development pattern to follow:

1. Create a personal fork of the main Merlin repository in GitHub.
2. Create a new feature branch (e.g., my-new-feature) to make your changes.
3. Generate a pull request through the GitHub web interface to merge your changes into the main branch.

Citation

If your work involves Merlin, please ensure to cite it properly:

Zhizheng Wu, Oliver Watts, Simon King, Merlin: An Open Source Neural Network Speech Synthesis System in Proc. 9th ISCA Speech Synthesis Workshop (SSW9), September 2016, Sunnyvale, CA, USA.

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