Audio Processorv1.0.0

Automate audio post-processing for podcasts including noise removal, volume normalization, and silence trimming. Batch convert podcast episodes to multiple formats for distribution.

Analyze student performances by extracting BPM, pitch, and spectral features. Provide slowed-down versions for practice without changing pitch.

Process recorded calls to detect silence, normalize volume, and convert formats for storage. Extract metadata for compliance and analysis.

Merge multiple audio chapters, apply fade in/out, and convert to standard audiobook formats (M4B). Detect and remove excessive silence between sections.

Prepare training datasets by batch converting and augmenting audio files (speed/pitch variation). Generate spectrograms and extract features for ASR model training.

Offer a web platform where users upload audio files and access processing scripts via API or GUI. Revenue from monthly subscriptions based on usage or number of projects.

Provide basic processing (format conversion, simple cuts) for free, charge for advanced features (noise reduction, multi-track merging, high-quality exports).

License the toolset to media companies or educational institutions for integration into their workflows. Offer training and customization (e.g., specific batch processing pipelines).