logWMSE, an audio quality metric & loss function with support for digital silence target. Useful for training and evaluating audio source separation systems.
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Updated
Jan 29, 2026 - Python
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
Collection of community-made presets for PulseEffects tailored for TUXEDO laptops.
Repository for subjective and objective evaluation of source separation algorithms
The code for the MAPSS measures for source separation evaluation (ICLR, 2026)
evalmedia is an open-source Python framework for evaluating the quality of AI-generated media (images, video, audio).
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Audio Analysis Tool - Real-time speech recognition, transcription and quality analysis with Vosk and SNR evaluation
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.
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