Search Results for "audio separation"
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Showing 11 open source projects for "audio separation"
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1
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). -
2
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. ... -
3
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. -
4
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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5
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. -
6
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. -
7
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. -
8
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. ... -
9
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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10
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. -
11
Spleeter
Deezer source separation library including pretrained models
...Spleeter is also very fast as it can perform separation of audio files to 4 stems 100x faster than real-time when run on a GPU. We designed Spleeter so you can use it straight from command line as well as directly in your own development pipeline as a Python library. It can be installed with Conda, with pip or be used with Docker.
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