Search Results for "audio separation"
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Showing 23 open source projects for "audio separation"
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Ultimate Vocal Remover (UVR5)
GUI for a Vocal Remover that uses Deep Neural Networks
This application uses state-of-the-art source separation models to remove vocals from audio files. UVR's core developers trained all of the models provided in this package (except for the Demucs v3 and v4 4-stem models). -
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Buzz
Buzz transcribes and translates audio offline
Buzz is a desktop application for transcribing and translating audio locally with speech recognition models based on Whisper. It can process audio files, video files, and YouTube links without requiring cloud transcription. Live microphone transcription supports real-time captions and a presentation view for accessible events. Speech separation can improve results on noisy recordings, while speaker identification distinguishes voices within transcribed media. ... -
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OpenVINO AI Plugins for Audacity
A set of AI-enabled effects, generators, and analyzers for Audacity
A set of AI-enabled effects, generators, and analyzers for Audacity. These AI features run 100% locally on your PC, no internet connection is necessary. OpenVINO™ is used to run AI models on supported accelerators found on the user's system such as CPU, GPU, and NPU. -
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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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Voice-Pro
Comprehensive Gradio WebUI for audio processing
Voice-Pro is the best gradio WebUI for transcription, translation and text-to-speech. It can be easily installed with one click. Create a virtual environment using Miniconda, running completely separate from the Windows system (fully portable). Supports real-time transcription and translation, as well as batch mode. -
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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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Whisper-WebUI
A Web UI for easy subtitle using whisper model
...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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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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Ultimate Mono2Stereo
A better mono to stereo audio conversion tool
What sets this frontend for ffmpeg apart from other stereo simulators is it creates an impression of stereo separation. Without trying too hard to be "true" stereo in a gimmicky fashion. More importantly, it produces none of the weird phasing, and/or time delay artifacts. And very little, if any of the tone discoloration, when those others aren't meticulously set up just right. All this is accomplished by using the ffmpeg crossover audio filter to split the sound into 8 frequency bands. ... -
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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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vocal-separate
An extremely simple tool for separating vocals and background music
...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. After processing, the tool outputs separate WAV files for each extracted stem, making it easy to export and use in audio editing or remix software. -
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Audio AI Timeline
A timeline of the latest AI models for audio generation
Audio AI Timeline is a curated project that organizes the development of audio-related artificial intelligence into a structured and accessible historical timeline. 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. ... -
13
Asteroid
The PyTorch-based audio source separation toolkit for researchers
The PyTorch-based audio source separation toolkit for researchers. Pytorch-based audio source separation toolkit that enables fast experimentation on common datasets. It comes with a source code thats supports a large range of datasets and architectures, and a set of recipes to reproduce some important papers. Building blocks are thought and designed to be seamlessly plugged together. -
14
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. MISST even comes prepared to import songs and playlists directly from your music library. -
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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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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
...Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. The repository includes all necessary scripts for training, dataset preparation, distributed training, evaluation, and audio separation. -
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ManyEars implements real-time microphone array processing to perform sound source localisation, tracking and separation. It was designed for mobile robot audition in dynamic environments. NOTE: Development will continue on github : https://github.com/introlab/manyears
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Streamripper records shoutcast-compatible streams. For shoutcast style streams it finds the "meta data" or track separation data, and uses that as a marker for where the track should be separated.
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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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TacitPixel is a scalable C++ framework for building application prototypes for interactive collaborative VR/AR applications. It provides a number of features that make prototyping fast and portable. TacitPixel is the successor of the TAP and Twisted Pair engines.
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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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