{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/5"},{"label":"Multimedia","url":"https://skillfed.io/packages/category/multimedia"},{"label":"Sound/Audio","url":"https://skillfed.io/packages/category/multimedia-sound-audio"},{"label":"Artistic Software","url":"https://skillfed.io/packages/category/artistic-software"},{"label":"Editors","url":"https://skillfed.io/packages/category/multimedia-sound-audio-editors"}],"enrichment":{"capability":"Compresses audio into discrete codes at 8 kbps bitrate and reconstructs it with high fidelity, supporting 16 kHz, 24 kHz, and 44.1 kHz sampling rates across speech, music, and environmental audio.","skillfed_tags":["audio-codec","neural-compression","generative-audio"],"use_cases":["Compress audio for storage or transmission while maintaining perceptual quality in generative audio models","Use as a backend codec for audio language models or music generation systems","Encode audio files into discrete codes for downstream machine learning tasks","Reconstruct high-fidelity audio from compressed .dac files for playback or further processing","Replace existing codecs in audio ML pipelines that require a universal codec across domains"],"what_it_does":"Descript Audio Codec is a neural audio codec that compresses audio into discrete codes at 8 kbps bitrate while preserving high fidelity. It uses an improved RVQGAN architecture and works universally across speech, music, and environmental audio. The package provides both command-line tools and a Python API for programmatic use via its runtime dependencies including torch, torchaudio, einops, numpy, argbind, descript-audiotools, and tqdm.\n\nThe codec is designed as a drop-in replacement for audio language modeling applications. Pre-trained model weights for 16 kHz, 24 kHz, and 44.1 kHz are automatically downloaded and cached on first use. The package is actively maintained and has no known vulnerabilities.","worth_installing":"Yes, if you need audio compression for ML applications. The codec is actively maintained, has no known vulnerabilities, uses a permissive MIT license, and offers strong compression with high fidelity. Install friction is low for developers already using PyTorch. Not suitable if you need real-time or streaming inference without GPU, or if you require lossless compression."},"id":"descript-audio-codec","links":{"html":"https://skillfed.io/packages/descript-audio-codec","md":"https://skillfed.io/packages/descript-audio-codec.md","pypi":"https://pypi.org/project/descript-audio-codec/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2023-07-20","license_spdx":null,"license_treatment":"permissive","name":"descript-audio-codec","python_support":"unspecified","summary":"A high-quality general neural audio codec."},"popularity":{"monthly_downloads":487316,"position":6387,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.0"}