mlsanityData to 14 Oct 2026

DNSMOS: A Non-Intrusive Perceptual Objective Speech Quality metric to evaluate Noise Suppressors

arXiv 2010.15258 ↗First posted 28 Oct 2020cs.SD cs.LG eess.AScited by 241

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Cited by 45 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Human subjective evaluation is the gold standard to evaluate speech quality optimized for human perception. Perceptual objective metrics serve as a proxy for subjective scores. The conventional and widely used metrics require a reference clean speech signal, which is unavailable in real recordings. The no-reference approaches correlate poorly with human ratings and are not widely adopted in the research community. One of the biggest use cases of these perceptual objective metrics is to evaluate noise suppression algorithms. This paper introduces a multi-stage self-teaching based perceptual objective metric that is designed to evaluate noise suppressors. The proposed method generalizes well in challenging test conditions with a high correlation to human ratings.

Key facts. Cited by 241 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Oct 2020.

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Citing papers per year: 2021: 12; 2022: 18; 2023: 21; 2024: 30; 2025: 69; 2026: 91.

241 papers.

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  1. 2023AudioPaLM: A Large Language Model That Can Speak and Listencited by 343
  2. 2022Speech Enhancement and Dereverberation with Diffusion-based Generative Modelscited by 197
  3. 2024VALL-E 2: Neural Codec Language Models are Human Parity Zero-Shot Text to Speech Synthesizerscited by 122
  4. 2021MetricGAN+: An Improved Version of MetricGAN for Speech Enhancementcited by 114
  5. 2023SoundStorm: Efficient Parallel Audio Generationcited by 114
  6. 2023SpeechX: Neural Codec Language Model as a Versatile Speech Transformercited by 64
  7. 2024EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberationcited by 64
  8. 2022HiFi++: a Unified Framework for Bandwidth Extension and Speech Enhancementcited by 49
  9. 2021Interspeech 2021 Deep Noise Suppression Challengecited by 47
  10. 2024Zero-shot Voice Conversion with Diffusion Transformerscited by 43
  11. 2026MOVA: Towards Scalable and Synchronized Video-Audio Generationcited by 43
  12. 2021Deep Learning-based Non-Intrusive Multi-Objective Speech Assessment Model with Cross-Domain Featurescited by 33
38 more
  1. 2025VABench: A Comprehensive Benchmark for Audio-Video Generationcited by 30
  2. 2021Unsupervised Speech Enhancement using Dynamical Variational Auto-Encoderscited by 28
  3. 2024MaskSR: Masked Language Model for Full-band Speech Restorationcited by 24
  4. 2022CMGAN: Conformer-Based Metric-GAN for Monaural Speech Enhancementcited by 23
  5. 2024SimpleSpeech: Towards Simple and Efficient Text-to-Speech with Scalar Latent Transformer Diffusion Modelscited by 23
  6. 2024SpoofCeleb: Speech Deepfake Detection and SASV In The Wildcited by 22
  7. 2025AudioJudge: Understanding What Works in Large Audio Model Based Speech Evaluationcited by 21
  8. 2022SpeechLMScore: Evaluating speech generation using speech language modelcited by 20
  9. 2021MetricGAN-U: Unsupervised speech enhancement/ dereverberation based only on noisy/ reverberated speechcited by 18
  10. 2024SimpleSpeech 2: Towards Simple and Efficient Text-to-Speech with Flow-based Scalar Latent Transformer Diffusion Modelscited by 17
  11. 2025InstructTTSEval: Benchmarking Complex Natural-Language Instruction Following in Text-to-Speech Systemscited by 17
  12. 2021Unsupervised Noise Adaptive Speech Enhancement by Discriminator-Constrained Optimal Transportcited by 16
  13. 2025TASTE: Text-Aligned Speech Tokenization and Embedding for Spoken Language Modelingcited by 16
  14. 2024StreamVC: Real-Time Low-Latency Voice Conversioncited by 15
  15. 2025ContextASR-Bench: A Massive Contextual Speech Recognition Benchmarkcited by 15
  16. 2023Self-Supervised Visual Acoustic Matchingcited by 14
  17. 2025NonverbalTTS: A Public English Corpus of Text-Aligned Nonverbal Vocalizations with Emotion Annotations for Text-to-Speechcited by 14
  18. 2023Unsupervised speech enhancement with diffusion-based generative modelscited by 12
  19. 2025AudioGen-Omni: A Unified Multimodal Diffusion Transformer for Video-Synchronized Audio, Speech, and Song Generationcited by 12
  20. 2022Music Enhancement via Image Translation and Vocodingcited by 11
  21. 2024Unsupervised Blind Joint Dereverberation and Room Acoustics Estimation with Diffusion Modelscited by 11
  22. 2024Generative Pre-trained Speech Language Model with Efficient Hierarchical Transformercited by 10
  23. 2025Survey on the Evaluation of Generative Models in Musiccited by 10
  24. 2025Towards Interactive Intelligence for Digital Humanscited by 10
  25. 2024BUDDy: Single-Channel Blind Unsupervised Dereverberation with Diffusion Modelscited by 9
  26. 2024End-to-end streaming model for low-latency speech anonymizationcited by 9
  27. 2025From Faces to Voices: Learning Hierarchical Representations for High-quality Video-to-Speechcited by 9
  28. 2021TUNet: A Block-online Bandwidth Extension Model based on Transformers and Self-supervised Pretrainingcited by 8
  29. 2022ESPnet-SE++: Speech Enhancement for Robust Speech Recognition, Translation, and Understandingcited by 8
  30. 2023TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognitioncited by 8
  31. 2023DDTSE: Discriminative Diffusion Model for Target Speech Extractioncited by 8
  32. 2024Diffusion-based Speech Enhancement with Schr"odinger Bridge and Symmetric Noise Schedulecited by 8
  33. 2024High-Resolution Speech Restoration with Latent Diffusion Modelcited by 8
  34. 2021REAL-M: Towards Speech Separation on Real Mixturescited by 7
  35. 2021InQSS: a speech intelligibility and quality assessment model using a multi-task learning networkcited by 7
  36. 2022End-to-End Neural Speech Coding for Real-Time Communicationscited by 7
  37. 2023Dynamic nsNet2: Efficient Deep Noise Suppression with Early Exitingcited by 7
  38. 2023Diffusion-based speech enhancement with a weighted generative-supervised learning losscited by 7

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