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Audio Quality Assessment

Computational audio quality assessment aims to predict the quality of audio signals as perceived by expert listeners.

Papers

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Showing 1–10 of 15 papers

TitleStatusHype
PAM: Prompting Audio-Language Models for Audio Quality AssessmentCode2
Perceiving Music Quality with GANsCode1
HAAQI-Net: A Non-intrusive Neural Music Audio Quality Assessment Model for Hearing AidsCode1
ODAQ: Open Dataset of Audio QualityCode1
ODAQ: Open Dataset of Audio Quality - Benchmark on GitHubCode1
P.862.2 : Wideband extension to Recommendation P.862 for the assessment of wideband telephone networks and speech codecsCode1
SAQAM: Spatial Audio Quality Assessment Metric—0
Towards Improved Objective Perceptual Audio Quality Assessment -- Part 1: A Novel Data-Driven Cognitive Model—0
A Data-driven Cognitive Salience Model for Objective Perceptual Audio Quality Assessment—0
Uncertainty as a Predictor: Leveraging Self-Supervised Learning for Zero-Shot MOS Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NMRPearson correlation coefficient (PCC)0.89—Unverified
2PEAQ-CSMPearson correlation coefficient (PCC)0.89—Unverified
32f-modelPearson correlation coefficient (PCC)0.87—Unverified
4PEAQ (ODG)Pearson correlation coefficient (PCC)0.87—Unverified
5ViSQOLAudioV3Pearson correlation coefficient (PCC)0.77—Unverified
6SMAQPearson correlation coefficient (PCC)0.77—Unverified
7PESQPearson correlation coefficient (PCC)0.74—Unverified
8SI-SDRPearson correlation coefficient (PCC)0.44—Unverified
9DNSMOS (OVRL)Pearson correlation coefficient (PCC)0.38—Unverified