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NOMAD: Unsupervised Learning of Perceptual Embeddings for Speech Enhancement and Non-matching Reference Audio Quality Assessment.

, , and . CoRR, (2023)

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Audio Inpainting based on Self-similarity for Sound Source Separation Applications., , and . MMSP, page 1-6. IEEE, (2020)Reduce, Reuse, Recycle: Is Perturbed Data better than Other Language augmentation for Low Resource Self-Supervised Speech Models., , and . CoRR, (2023)Learning Music Representations with wav2vec 2.0., , and . AICS, page 1-6. IEEE, (2023)AQP: An Open Modular Python Platform for Objective Speech and Audio Quality Metrics., , , and . CoRR, (2021)Fusion confusion: exploring ambisonic spatial localisation for audio-visual immersion using the McGurk effect., , , and . MMVE@MMSys, page 28-33. ACM, (2019)AQP: an open modular Python platform for objective speech and audio quality metrics., , , and . MMSys, page 191-196. ACM, (2022)Adapting the Quality of Experience Framework for Audio Archive Evaluation., , and . QoMEX, page 1-3. IEEE, (2019)Exploring the influence of fine-tuning data on wav2vec 2.0 model for blind speech quality prediction., , and . INTERSPEECH, page 4088-4092. ISCA, (2022)Audio Impairment Recognition using a Correlation-Based Feature Representation., , and . QoMEX, page 1-6. IEEE, (2020)NOMAD: Unsupervised Learning of Perceptual Embeddings for Speech Enhancement and Non-matching Reference Audio Quality Assessment., , and . CoRR, (2023)