Audio
pyannote-audio
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
★ 10,6 Tsd. SterneMIT
Anleitung ansehen →torch-log-wmse ist ein Open-Source-Projekt aus der Kategorie KI-Musik von crlandsc (crlandsc/torch-log-wmse auf GitHub). Es hat 50 Sterne auf GitHub und 1 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 1. September 2026 auf GitHub aktualisiert.
An audio quality metric and loss for training cleaner models.
Add it to your training environment.
Use it as a loss or metric.
Configure digital-silence behavior.
Optimize your audio model with it.
Audio quality measurement in PyTorch.
Train directly against it.
Handles digital silence correctly.
Built for enhancement tasks.
Works for source-separation training.
Free for research and products.
Download the source and enter the folder.
git clone https://github.com/crlandsc/torch-log-wmse.git
cd torch-log-wmseInstall the Python package.
pip install -e .Import logWMSE in your loop.
python -c "import torch_log_wmse; print(torch_log_wmse.__file__)"logWMSE, an audio quality metric and loss function for PyTorch, at crlandsc/torch-log-wmse.
Training and evaluating audio models like denoisers and separators.
Training targets where the correct output is silence; the metric handles them properly.
Yes. Apache-2.0 licensed.
Audio ML researchers and engineers training enhancement models.
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio…
Real-time, low-latency music source separation in PyTorch.
Loss functions for training audio source separation models.
Stable Audio Tools — training and inference code for Stability's audio generation models, including Stable Audio Open, MIT
Friendly front-end for local AI music models, packed with quality-of-life touches.
Die anderen Projekte der Kategorie KI-Musik mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls torch-log-wmse nicht das Richtige ist.
YuE2: frontier music generation with symbolic planning, zero-shot covers, and agentic music editing.
🎵 The Ultimate Open Source Suno Alternative - Professional UI for ACE-Step 1.5 AI Music Generation. Free, local, unlimited. Stop paying for Suno!
ACE-Step — the open foundation model for music generation: full songs with vocals and lyrics in 19 languages, up to 4 minutes in about 20 seconds, Apache-2.0
Official DiffSinger code: diffusion-based singing voice synthesis and text-to-speech (AAAI 2022)
Stable Audio Tools — training and inference code for Stability's audio generation models, including Stable Audio Open, MIT
Verwandte Projekte der Kategorie KI-Musik im Katalog, die torch-log-wmse bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
An ESP32 hardware metronome with a web UI.
Open-source AI music SaaS: full tracks with cover art from a text prompt.
MCP server for AI-generated MIDI — text in, compositions out.
Run splifft locally: lightweight utilities for music source separation and t.
Terminal client for Suno v5.5 — tags, vocal control, and full generation flags.
Run stemgen-rt locally: stemgenrt is a real-time low-latency music source separ.
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.