{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"},{"label":"Sound/Audio","url":"https://skillfed.io/packages/category/multimedia-sound-audio"}],"enrichment":{"capability":"Embeds imperceptible watermarks into audio files and detects them afterward, using neural network-based techniques that survive common audio transformations.","skillfed_tags":["audio-processing","watermarking","neural-networks"],"use_cases":["Embed ownership or authenticity markers in audio content for copyright protection or provenance tracking.","Detect whether audio has been watermarked as part of a content verification or anti-piracy workflow.","Test audio watermarking robustness by applying transformations and checking if watermarks survive.","Evaluate perceptual quality of watermarked audio using built-in metrics before deploying to production.","Integrate watermarking into an audio processing pipeline via the Python API."],"what_it_does":"Perth is a Python library for embedding and extracting imperceptible watermarks in audio files. It implements neural network-based watermarking techniques\u2014primarily the Perth-Net Implicit approach\u2014designed to survive audio transformations like compression and resampling while maintaining perceptual audio quality. The library provides both a command-line interface for quick tasks and a Python API for integration into applications.\n\nYou load audio, initialize a watermarker object, apply or extract a watermark, and save the result. The package includes utilities to measure audio quality metrics and compare original and watermarked audio. It supports Python 3.8, 3.9, 3.10, and 3.11 and has no runtime dependencies, making installation straightforward.","worth_installing":"Yes, if you need audio watermarking. The library has low install friction, permissive licensing, no known vulnerabilities, and an active repository. However, the aging maintenance status and lack of recent updates suggest you should verify that the neural network models and robustness claims meet your specific use case before committing to production deployment."},"id":"resemble-perth","links":{"html":"https://skillfed.io/packages/resemble-perth","md":"https://skillfed.io/packages/resemble-perth.md","pypi":"https://pypi.org/project/resemble-perth/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-05-23","license_spdx":null,"license_treatment":"permissive","name":"resemble-perth","python_support":"supports_current","summary":"Audio Watermarking and Detection Library"},"popularity":{"monthly_downloads":239877,"position":8913,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.1"}