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Human subjective evaluation is the gold standard to evaluate speech quality optimized for human perception.
Feb 1998
“Itu-t recommendation p.800: Methods for subjective determination of transmission quality, itu-t recommendation p.800,” · 1998
Earlier work this paper cites.
“Perceptual evaluation of speech quality (pesq)-a new method for speech quality assessment of telephone networks and codecs,”
A. W. Rix, J. G. Beerends, M. P. Hollier, and A. P. Hekstra, · 2001
Earlier work this paper cites.
“P. 1401, methods, metrics and procedures for statistical evaluation, qualification and comparison of objective quality prediction models,”
ITUT Rec, · 2012
Earlier work this paper cites.
“Perceptual objective listening quality assessment (polqa), the third generation itu-t standard for end-to-end speech quality measurement part ii-perceptual model,”
John Beerends, Christian Schmidmer, Jens Berger, Matthias Obermann, Raphael Ullmann, Joachim Pomy, and Michael Keyhl, · 2013
Earlier work this paper cites.
“Speech acoustic modeling from raw multichannel waveforms,”
Y. Hoshen, R. J. Weiss, and K. W. Wilson, · 2015
Earlier work this paper cites.
“Deep learning is robust to massive label noise,”
David Rolnick, Andreas Veit, Serge J. Belongie, and Nir Shavit, · 2017
Earlier work this paper cites.
“A scalable noisy speech dataset and online subjective test framework,”
Chandan KA Reddy, Ebrahim Beyrami, Jamie Pool, Ross Cutler, Sriram Srinivasan, and Johannes Gehrke, · 2019
Cited alongside, same era.
“Intrusive and non-intrusive perceptual speech quality assessment using a convolutional neural network,”
Hannes Gamper, Chandan KA Reddy, Ross Cutler, Ivan J Tashev, and Johannes Gehrke, · 2019
Cited alongside, same era.
“Non-intrusive speech quality assessment using neural networks,”
A. R. Avila, H. Gamper, C. Reddy, R. Cutler, I. Tashev, and J. Gehrke, · 2019
Cited alongside, same era.
“Continual lifelong learning with neural networks: A review,”
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter, · 2019
Cited alongside, same era.
“Supervised classifiers for audio impairments with noisy labels,”
Chandan KA Reddy, Ross Cutler, and Johannes Gehrke, · 2019
Cited alongside, same era.
“An attention enhanced multi-task model for objective speech assessment in real-world environments,”
Xuan Dong and Donald S Williamson, · 2020
Closest in time.
“A differentiable perceptual audio metric learned from just noticeable differences,”
Pranay Manocha, Adam Finkelstein, Zeyu Jin, Nicholas J Bryan, Richard Zhang, and Gautham J Mysore, · 2020
Closest in time.
“An open source implementation of itu-t recommendation p.808 with validation,” 2020
Babak Naderi and Ross Cutler, · 2020
Closest in time.
Chandan KA Reddy, Vishak Gopal, Ross Cutler, Ebrahim Beyrami, Roger Cheng, Harishchandra Dubey, Sergiy Matusevych, Robert Aichner, Ashkan Aazami, Sebastian Braun, et al., · 2020
Closest in time.
“Real time speech enhancement in the waveform domain,” 2020
Alexandre Defossez, Gabriel Synnaeve, and Yossi Adi, · 2020
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Kou Tanaka, Hirokazu Kameoka, Takuhiro Kaneko, and Nobukatsu Hojo, · 2019
Cited alongside, same era.
“A sequential self teaching approach for improving generalization in sound event recognition,”
Anurag Kumar and Vamsi Krishna Ithapu,
Cited in the paper.
Closest in time.
“Icassp 2021 deep noise suppression challenge,”
Chandan K A Reddy, Harishchandra Dubey, Vishak Gopal, Ross Cutler, Sebastian Braun, Hannes Gamper, Robert Aichner, and Sriram Srinivasan, · 2020
Closest in time.