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Within the area of speech enhancement, there is an ongoing interest in the creation of neural systems which explicitly aim to improve the perceptual quality of the processed audio.
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C. Valentini-Botinhao, “Noisy speech database for training speech enhancement algorithms and tts models,” 2017. [Online]. Available: https://doi.org/10.7488/ds/2117
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G. Mittag, R. Cutler, Y. Hosseinkashi, M. Revow, S. Srinivasan, N. Chande, and R. Aichner, “DNN No-Reference PSTN Speech Quality Prediction,” in Interspeech 2020
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Y. Luo, Z. Chen, and T. Yoshioka, “Dual-Path RNN: Efficient Long Sequence Modeling for Time-Domain Single-Channel Speech Separation,” in ICASSP 2020
2020
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G. Mittag, B. Naderi, A. Chehadi, and S. Möller, “NISQA: A deep CNN-self-attention model for multidimensional speech quality prediction with crowdsourced datasets,” in Interspeech 2021
2021
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S.-W. Fu, C. Yu, T.-A. Hsieh, P. Plantinga, M. Ravanelli, X. Lu, and Y. Tsao, “MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement,” in Interspeech 2021
2021
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C. K. A. Reddy, V. Gopal, and R. Cutler, “Dnsmos: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors,” in ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2021, pp. 6493–6497
2021
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Santiago Cuervo, Ricard Marxer, “Temporal-hierarchical features from noise-robust speech foundation models for non-intrusive intelligibility prediction,” in Clarity Workshop 2022 . [Online]. Available: https://claritychallenge.org/clarity2023-workshop/papers/CPC2_E011_report.pdf
2022
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F. Dang, H. Chen, and P. Zhang, “DPT-FSNet: Dual-Path Transformer Based Full-Band and Sub-Band Fusion Network for Speech Enhancement,” in ICASSP 2022
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A. Kumar, K. Tan, Z. Ni, P. Manocha, X. Zhang, E. Henderson, and B. Xu, “Torchaudio-Squim: Reference-Less Speech Quality and Intelligibility Measures in Torchaudio,” ICASSP 2023
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S. Leglaive, L. Borne, E. Tzinis, M. Sadeghi, M. Fraticelli, S. Wisdom, M. Pariente, D. Pressnitzer, and J. R. Hershey, “The CHiME-7 UDASE task: Unsupervised domain adaptation for conversational speech enhancement,” 2023
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S.-W. Fu, C. Yu, K.-H. Hung, M. Ravanelli, and Y. Tsao, “MetricGAN-U: Unsupervised Speech Enhancement/ Dereverberation Based Only on Noisy/ Reverberated Speech,” in ICASSP 2022
2022
Cited alongside, same era.
G. Yi, W. Xiao, Y. Xiao, B. Naderi, S. Möller, W. Wardah, G. Mittag, R. Cutler, Z. Zhang, D. S. Williamson et al. , “ConferencingSpeech 2022 Challenge: Non-intrusive Objective Speech Quality Assessment (NISQA) Challenge for Online Conferencing Applications,” 2022
2022
Cited alongside, same era.
G. Close, T. Hain, and S. Goetze, “MetricGAN+/-: Increasing Robustness of Noise Reduction on Unseen Data,” in EUSIPCO 2022 , Belgrade, Serbia, Aug. 2022
2022
Cited alongside, same era.
G. Close, S. Hollands, T. Hain, and S. Goetze, “Non-intrusive Speech Intelligibility Metric Prediction for Hearing Impaired Individuals,” in Proc. Interspeech 2022 , 2022, pp. 3483–3487
2022
Cited alongside, same era.
A. Radford, J. W. Kim, T. Xu, G. Brockman, C. McLeavey, and I. Sutskever, “Robust Speech Recognition via Large-Scale Weak Supervision,” 2022
2022
Cited alongside, same era.
G. Close, W. Ravenscroft, T. Hain, and S. Goetze, “CMGAN+/+: The University of Sheffield CHiME-7 UDASE Challenge Speech Enhancement System,” in Proc. 7th Int. Workshop on Speech Processing in Everyday Environments (CHiME 2023) , Dublin, Ireland, Aug. 2023
2023
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B. Tamm, R. Vandenberghe, and H. Van hamme, “Analysis of xls-r for speech quality assessment,” 2023
2023
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K. Shen, D. Yan, and L. Dong, “Msqat: A multi-dimension non-intrusive speech quality assessment transformer utilizing self-supervised representations,” Applied Acoustics , 2023
2023
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S. Leglaive, M. Fraticelli, H. ElGhazaly, L. Borne, M. Sadeghi, S. Wisdom, M. Pariente, J. R. Hershey, D. Pressnitzer, and J. P. Barker, “Objective and subjective evaluation of speech enhancement methods in the udase task of the 7th chime challenge,” 2024
2024
Closest in time.
R. Mogridge, G. Close, R. Sutherland, T. Hain, J. Barker, S. Goetze, and A. Ragni, “Non-intrusive speech intelligibility prediction for hearing-impaired users using intermediate asr features and human memory models,” in Proc. ICASSP 2024 (accepted) , 2024
2024
Closest in time.