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Welcome to Whombat

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Welcome to the Whombat documentation, your go-to resource for understanding and utilizing this open-source audio annotation tool tailored for ML development.

If you're eager to dive into using Whombat, explore the User Guide for comprehensive instructions.

Why Whombat?

In the realm of audio analysis tools, numerous options exist, each with its specific strengths. Tools like Raven and Audacity excel at audio analysis but might fall short when it comes to the specialized needs of audio annotation for machine learning development. Whombat bridges this gap by focusing on the following key requirements:

  1. Evolving Datasets: Whombat empowers you to build and manage enduring datasets of audio recordings, accommodating changes and updates as your project evolves.

  2. Structured Annotation Projects: Create well-defined annotation projects, complete with clear instructions and tasks. Track progress and ensure consistency across your team.

  3. Annotation Review: Thoroughly examine and validate existing annotations to maintain data quality.

  4. Import/Export Flexibility: Import and export annotations in various formats, facilitating collaboration and integration with other tools.

  5. Flexible Annotation: Annotate sounds with precision, specifying Regions of Interest (ROIs) using bounding boxes, intervals, or other methods. Attach rich metadata to annotations, including tags and notes.

  6. Sound Exploration: Explore your sound collection to uncover patterns and gain insights. Facilitate sound identification and classification through interactive tools.

  7. Model Comparison: Compare model outputs with human annotations to identify areas where your model is underperforming and pinpoint where additional annotation is needed.

Whombat's design prioritizes careful, manual data curation. We believe this emphasis on precision will enable the community to build gold-standard bioacoustic datasets, fueling the development of cutting-edge machine learning models.

Get started quickly

New to Whombat? Here’s how you can get up and running:

  1. Install Whombat: Set up the tool on your machine.
  2. Try the Example Data: Take a hands-on tour by importing our example project, it's the fastest way to see Whombat in action.
  3. Explore the User Guide: Learn about Core Concepts and discover Practical Guides & Workflows for your annotation tasks.
  4. Got Questions? Visit our FAQ.

For Developers & Contributors

Want to dive deeper into Whombat's internals, integrate it with Python, or contribute back?

  • Explore the Developer Guide (Coming Soon!) for insights into the architecture and development practices.
  • Consult the Reference section for detailed technical documentation.
  • Learn how you can contribute by reading our Contributing Guidelines.

Warning

Please bear with us, as this documentation is a work in progress, and we're working hard to smooth out any rough edges.