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In recent years, Generative Adversarial Networks (GANs) have produced significantly improved results in speech enhancement (SE) tasks.
“All-pole modeling of degraded speech,”
J. Lim and A. Oppenheim, · 1978
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“Suppression of acoustic noise in speech using spectral subtraction,”
S. Boll, · 1979
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“Perceptual evaluation of speech quality (pesq)-a new method for speech quality assessment of telephone networks and codecs,”
A. Rix, J. Beerends, M. Hollier, and A. Hekstra, · 2001
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“Evaluation of objective quality measures for speech enhancement,”
Y. Hu and P. Loizou, · 2008
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“Fast signal reconstruction from magnitude stft spectrogram based on spectrogram consistency,”
J. Le Roux, H. Kameoka, N. Ono, and S. Sagayama, · 2010
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“A short-time objective intelligibility measure for time-frequency weighted noisy speech,”
C. Taal, R. Hendriks, R. Heusdens, and J. Jensen, · 2010
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“The voice bank corpus: Design, collection and data analysis of a large regional accent speech database,”
C. Veaux, J. Yamagishi, and S. King, · 2013
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“The diverse environments multi-channel acoustic noise database (demand): A database of multichannel environmental noise recordings,”
J. Thiemann, N. Ito, and E. Vincent, · 2013
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“Investigating rnn-based speech enhancement methods for noise-robust text-to-speech,”
C. Valentini-Botinhao, X. Wang, S. Takaki, and J. Yamagishi, · 2016
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“Segan: Speech enhancement generative adversarial network,” 2017
S. Pascual, A. Bonafonte, and J. Serrà, · 2017
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“Attention is all you need,”
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. Gomez, L. Kaiser, and I. Polosukhin, · 2017
Cited alongside, same era.
“Differentiable consistency constraints for improved deep speech enhancement,”
S. Wisdom, J. Hershey, K. Wilson, J. Thorpe, M. Chinen, B. Patton, and R. Saurous, · 2019
Cited alongside, same era.
“Low-latency single channel speech enhancement using u-net convolutional neural networks,”
A. E. Bulut and K. Koishida, · 2020
Cited alongside, same era.
“Single-channel speech enhancement by subspace affinity minimization.,”
D. Tran and K. Koishida, · 2020
Cited alongside, same era.
H. Li, S.-W. Fu, Y. Tsao, and J. Yamagishi, · 2020
Cited alongside, same era.
“Towards efficient models for real-time deep noise suppression,”
S. Braun, H. Gamper, C. Reddy, and I. Tashev, · 2021
Later among the works it cites.
“Investigating cross-domain losses for speech enhancement,”
S. Abdulatif, K. Armanious, Ja. Thaiparambil Sajeev, K. Guirguis, and B. Yang, · 2021
Later among the works it cites.
“A consolidated view of loss functions for supervised deep learning-based speech enhancement,”
S. Braun and I. Tashev, · 2021
Later among the works it cites.
“Cmgan: Conformer-based metric gan for speech enhancement,”
R. Cao, S. Abdulatif, and B. Yang, · 2022
Closest in time.
“Dual-branch attention-in-attention transformer for single-channel speech enhancement,”
G. Yu, A. Li, C. Zheng, Y. Guo, Y. Wang, and H. Wang, · 2022
Closest in time.
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A. Gulati, J. Qin, C.-C. Chiu, N. Parmar, Y. Zhang, J. Yu, W. Han, S. Wang, Z. Zhang, Y. Wu, and R. Pang, · 2020
Cited alongside, same era.
“Metricgan+: An improved version of metricgan for speech enhancement,”
S.-W. Fu, C. Yu, T.-A. Hsieh, P. Plantinga, M. Ravanelli, X. Lu, and Y. Tsao, · 2021
Cited alongside, same era.
“Se-conformer: Time-domain speech enhancement using conformer,”
E. Kim and H. Seo, · 2021
Cited alongside, same era.
“Adaptive weighted discriminator for training gans,”
V. Zadorozhnyy, Q. Cheng, and Q. Ye, · 2021
Cited alongside, same era.
“Dpt-fsnet: Dual-path transformer based full-band and sub-band fusion network for speech enhancement,”
F. Dang, H. Chen, and P. Zhang, · 2022
Closest in time.
“Manner: Multi-view attention network for noise erasure,”
H. J. Park, B. H. Kang, W. Shin, J. S. Kim, and S. W. Han, · 2022
Closest in time.
“Perceptual contrast stretching on target feature for speech enhancement,”
R. Chao, C. Yu, S.-W. Fu, X. Lu, and Y. Tsao, · 2022
Closest in time.
“MetricGAN: Generative adversarial networks based black-box metric scores optimization for speech enhancement,”
S.-W. Fu, C.-F. Liao, Y. Tsao, and S.-D. Lin, · 2041
Closest in time.