Search Results for "music separation"
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Showing 16 open source projects for "music separation"
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Librosa
Python library for audio and music analysis
Librosa is a powerful Python library for analyzing and processing audio and music signals. Built on top of NumPy, SciPy, and matplotlib, it provides a wide range of tools for feature extraction, time-series manipulation, audio display, and music information retrieval. Whether you're building machine learning models for audio classification or visualizing spectrograms, Librosa is a go-to library for researchers and developers working in audio signal processing. -
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MusicFreePlugins
MusicFreePlayPlugin
The MusicFreePluginsc project is a collection and framework for plugins that extend the functionality of the MusicFree ecosystem by providing access to various music sources and features. It defines a standardized interface for plugin development, allowing contributors to implement features such as search, playback, and metadata retrieval. The system is designed to be modular, enabling users to install, update, and manage plugins independently of the core application. It supports multiple... -
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audioFlux
A library for audio and music analysis, feature extraction
...It can be provided to deep learning networks for training and is used to study various tasks in the audio field such as Classification, Separation, Music Information Retrieval(MIR) ASR, etc. -
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TTS WebUI
A single Gradio + React WebUI with extensions for ACE-Step
TTS-WebUI is a unified Gradio + React web interface that brings together a large ecosystem of text-to-speech, voice conversion, and audio generation models under a single UI. It supports a wide range of models such as Bark, MusicGen, Tortoise, RVC, StyleTTS2, ParlerTTS, CosyVoice, XTTSv2, Stable Audio, SeamlessM4T, and many others, exposing them as interchangeable backends for speech and music synthesis. The project provides an installer that sets up Conda, Python environments, and all... -
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Whisper-WebUI
A Web UI for easy subtitle using whisper model
...It supports multiple input sources including local files, YouTube content, and microphone input, making it versatile for different workflows. Whisper WebUI also includes advanced preprocessing and postprocessing features such as voice activity detection, background music separation, and speaker diarization, enabling more accurate and structured outputs. -
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FL Studio
The best music production software
FL Studio by Image-Line is a complete digital audio workstation (DAW) designed to turn your musical ideas into professional-quality tracks with ease. Trusted by world-renowned artists like Martin Garrix, Mustard, and Boi-1da, it’s built for producers of every genre — from EDM and hip-hop to pop and cinematic music. With an intuitive interface and powerful workflow, you can start creating in minutes while exploring endless possibilities as your skills grow. FL Studio comes packed with over... -
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vocal-separate
An extremely simple tool for separating vocals and background music
vocal-separate is a simple but effective audio processing application that isolates vocals and instrumental tracks from music and video files using stem-based source separation models, enabling tasks such as karaoke creation, remixing, and music analysis. Built as a localized web-based tool, it runs entirely on the user’s machine without requiring an internet connection, emphasizing privacy and convenience for creative work. Users can drag and drop an audio or video file onto the interface to begin separation, choosing between two, four, or five stems, which allows isolating specific components like vocals, bass, drums, or piano depending on the chosen model. ... -
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Audio AI Timeline
A timeline of the latest AI models for audio generation
...Rather than functioning as a model training framework, it serves as an informational resource that maps key papers, systems, models, datasets, and milestones across areas such as speech synthesis, music generation, audio understanding, source separation, and general audio machine learning. The project helps users understand how major techniques and ideas evolved over time, making it especially useful for researchers, students, and practitioners who want a broad overview of the field without digging through scattered references. ... -
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Demucs
Code for the paper Hybrid Spectrogram and Waveform Source Separation
Demucs (Deep Extractor for Music Sources) is a deep-learning framework for music source separation—extracting individual instrument or vocal tracks from a mixed audio file. The system is based on a U-Net-like convolutional architecture combined with recurrent and transformer elements to capture both short-term and long-term temporal structure. It processes raw waveforms directly rather than spectrograms, allowing for higher-quality reconstruction and fewer artifacts in separated tracks. ... -
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MISST
A local GUI music source separation tool built on Tkinter and public F
MISST : Music/Instrumental Stem Separation Tool. This application uses state-of-the-art source separation models to extract the 4 core stems from audio files (Bass, Drums, Other Instrumentals and Vocals). But it is not limited to this. MISST acts as a developped music player aswell, fit to enjoy and medal with your audio files as you see fit. -
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audioFlux
A library for audio and music analysis, feature extraction.
audioflux is a deep learning tool library for audio and music analysis, feature extraction. It supports dozens of time-frequency analysis transformation methods and hundreds of corresponding time-domain and frequency-domain feature combinations. It can be provided to deep learning networks for training, and is used to study various tasks in the audio field such as Classification, Separation, Music Information Retrieval(MIR) and ASR etc. -
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Music Source Separation
Separate audio recordings into individual sources
Music Source Separation is a PyTorch-based open-source implementation for the task of separating a music (or audio) recording into its constituent sources — for example isolating vocals, instruments, bass, accompaniment, or background from a mixed track. It aims to give users the ability to take any existing song and decompose it into separate stems (vocals, accompaniment, etc.), or to train custom separation models on their own datasets (e.g. for speech enhancement, instrument isolation, or other audio-separation tasks). ... -
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Spleeter
Deezer source separation library including pretrained models
Spleeter is the Deezer source separation library with pretrained models written in Python and using Tensorflow. It makes it easy to train music source separation models (assuming you have a dataset of isolated sources), and provides already trained state of the art models for performing various flavours of separation. 2 stems and 4 stems models have state of the art performances on the musdb dataset. -
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ISSE
An Interactive Source Separation Editor
In applications such as audio denoising, music transcription, music remixing, and audio-based forensics, it is desirable to decompose a single-channel recording into its respective sources. To perform such tasks, we present a new software tool to perform source separation by painting on time-frequency visualizations of sound. Initial results shows the software can achieve state-of-the-art separation results compared to prior work. -
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StationRipper, based off of streamripper, records up to 300 simultaneous Shoutcast streams. Supports Track Separation, Scheduling, Memory Recording, play integration via Shoutcast.com, MP3 player access, easy rip restarts, and a music library manager.
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The Java based Shoutcast-Icecast Stream Grabber supports recording of up to 10 simultaneous streams. It enables you to record a complete song even when you notice in the middle of the song that you like it and supports track separation using meta data.
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