logWMSE, an audio quality metric & loss function with support for digital silence target. Useful for training and evaluating audio source separation systems.

Variations of L1 SNR Loss function for training audio source separation machine learning models

Unofficial PyTorch implementation of "Moises-Light: Resource-efficient Band-split U-Net For Music Source Separation"

Collection of community-made presets for PulseEffects tailored for TUXEDO laptops.

The code for the MAPSS measures for source separation evaluation (ICLR, 2026)

Repository for subjective and objective evaluation of source separation algorithms

evalmedia is an open-source Python framework for evaluating the quality of AI-generated media (images, video, audio).

best stereo plugin for better discord

MicLock fixes bad Mac Bluetooth headphone sound quality by preventing AirPods, Sony WH-1000XM and other headsets from becoming the default microphone.

Create a Dolby.io Frontend Application To Display Waveform With Wavesurfer.js And Interactive Elements Using Konva In SolidJS

Bulk upgrade your music library from lossy to lossless FLAC via Soulseek and SLSKD

A pure Python implementation of Google's ViSQOL (Virtual Speech Quality Objective Listener) for objective audio/speech quality assessment.

CLI-first deterministic audio/video quality gate. Catches corrupted, invalid, or low-quality media before it reaches humans.

Hallucination detection for voice agents — the independent audit layer for your STT, TTS, and full-duplex pipeline.

Free Windows app that detects fake lossless audio — MP3/AAC transcodes hiding in FLAC containers.

Application to Measure the Quality of Audio Devices using GNU Radio

Free audio quality analysis tool for the AI data industry. Quality scores, signal metrics, language detection, speaker diarization, and compliance checking.

Professional audio quality analyzer for Windows that scans and grades music libraries from S to F using FFmpeg-powered spectrum analysis. Detects upsampling artifacts, clipping, stereo phase issues, and evaluates loudness via EBU R128 with full batch processing and export support for CSV, JSON, and plain text reports.