NISQA - Non-Intrusive Speech Quality and TTS Naturalness Assessment
Python implementation of performance metrics in Loizou's Speech Enhancement book
VoIP signaling and media test automation
A toolkit to calculate speech audio quality. Not affiliated with the original authors
A Python library for computing the Mel-Cepstral Distance (Mel-Cepstral Distortion, MCD) between two inputs. This implementation is based on the method proposed by Robert F. Kubichek in "Mel-Cepstral Distance Measure for Objective Speech Quality Assessment".
Generate degraded speech datasets for noise-robust ASR benchmarking
Research toolkit for evaluating audio steganography and watermarking: payload recovery, signal quality, robustness, capacity and empirical detectability under a shared experimental protocol. Includes a Python API, declarative experiments and a browser-based research interface.
Deep Noise Suppression for Real Time Speech Enhancement in a Single Channel Wide Band Scenario
Objective measures of speech quality SNR
Train no-reference speech quality estimators with multiple datasets via learned, per-dataset alignments.
Go baresip wrapper for automated SIP tests
Python implementation of a few speech intelligibility prediction algorithms
Bias-Aware Loss for Training Image and Speech Quality Prediction Models from Multiple Dataset
A pure Python implementation of Google's ViSQOL (Virtual Speech Quality Objective Listener) for objective audio/speech quality assessment.
Know the quality of your speech
This repository belongs to my Bachelor's thesis on predicting voice likability from pre-trained speech embeddings.
Dataset of crowdsourced Speech Quality Assessment using the Comparison Category Rating (CCR) test method
PyTorch-free JAX inference for NISQA speech quality assessment, with bundled verified weights and tested CPU/CUDA support.
Mean Opinion Score analysis for TTS and AI dubbing listening tests: confidence intervals, rater normalisation, outlier raters, bootstrap ranking
Optimized PyTorch inference for NISQA speech quality and TTS naturalness models
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