Cross-platform, customizable ML solutions for live and streaming media.
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Updated
Oct 31, 2026 - C++
Cross-platform, customizable ML solutions for live and streaming media.
Deezer source separation library including pretrained models.
A PyTorch-based Speech Toolkit
3FUI 是 ffmpeg 在 Windows 上的轻度专业交互外壳,收录大量参数,界面美观,交互友好。此项目面向国内使用环境,让普通人也能够轻松压制视频和转换格式。
A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.
macOS System-wide Audio Equalizer & Volume Mixer 🎧
THIS REPO IS NOT MAINTAINED ANYMORE. Please see https://codeberg.org/tenacityteam/tenacity for Tenacity, which is maintained.
🎛 🔊 A Python library for audio.
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
AI audio watermark removal & forensic anti-attribution toolkit. Neutralizes Suno, Udio, and neural fingerprints with ISO 226 perceptual masking.
Effort free video editing!
An implementation of Shazam's song recognition algorithm.
An open-source Android Active Noise Cancellation (ANC) engine. Leveraging low-latency DSP to neutralize environmental hums and help you reclaim your quiet.
Local video editor for coding agents: 42 FFmpeg tools with a machine-readable contract and an MCP server, for Claude Code, Cursor and Codex. Cut, captions, reframe, loudness, platform exports. No cloud, no API keys.
A library for audio and music analysis, feature extraction.
Isolate vocals, drums, bass, and other instrumental stems from any song
List of articles related to deep learning applied to music
🎵 🌈 Real-time LED strip music visualization using Python and the ESP8266 or Raspberry Pi
Data manipulation and transformation for audio signal processing, powered by PyTorch
Open-source, self-hosted file-processing tool. Convert, compress, OCR, transcribe & run local AI across image, video, audio, PDF & documents, via UI, REST API & pipelines. Your files never leave your network.
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