A new tool called WaveWash has been developed to address the common issue of dirty audio data in training speech models like Whisper and TTS. The software automates audio quality control and data preparation, offering features such as preset profiles for different speech tasks, automatic repairs for common audio defects, and segregation of clean, error, and duplicate files. WaveWash aims to streamline the process for developers by eliminating the need for manual audio inspection and custom scripting. AI
IMPACT Streamlines audio data preparation for speech models, potentially accelerating development cycles for AI applications involving voice.
RANK_REASON The cluster describes a new software tool designed to improve a specific part of the AI development workflow.
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- Boobalan Arjunan
- Confluence
- DEV Community
- EBU Recommendation R 128
- GitHub
- Microsoft SharePoint
- Node.js
- Python
- Text To Speech
- voice cloning
- WaveWash
- Whisper
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