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Research Article

Measurement and prediction of the acceptable noise level for single-microphone noise reduction algorithms

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Pages 299-308 | Received 23 Feb 2011, Accepted 22 Nov 2011, Published online: 09 Feb 2012

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Karrie Recker, Adriana Goyette & Jason Galster. (2020) Preferences for digital noise reduction and microphone mode settings in hearing-impaired listeners with low and high tolerances for background noise. International Journal of Audiology 59:2, pages 90-100.
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Foong Yen Chong & Lorienne M. Jenstad. (2018) A critical review of hearing-aid single-microphone noise-reduction studies in adults and children. Disability and Rehabilitation: Assistive Technology 13:6, pages 600-608.
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Ross J. Roeser. (2014) The ANL: Does it, or does it not?. International Journal of Audiology 53:1, pages 1-1.
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Steen Østergaard Olsen & K. Jonas Brännström. (2014) Does the acceptable noise level (ANL) predict hearing-aid use?. International Journal of Audiology 53:1, pages 2-20.
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Hsu-Chueh Ho, Yu-Hsiang Wu, Shih-Hsuan Hsiao, Elizabeth Stangl, Emily J. Lentz & Ruth A. Bentler. (2013) The equivalence of acceptable noise level (ANL) with English, Mandarin, and non-semantic speech: A study across the U.S. and Taiwan. International Journal of Audiology 52:2, pages 83-91.
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Articles from other publishers (21)

Xu Jun Hu & Chi Chuen Lau. (2023) Influence of Speech Recognition Ability on Acceptable Noise Level for Mandarin (Chinese) Speakers with Normal Hearing. Audiology and Neurotology, pages 1-9.
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Donghyeon Yun, Yi Shen & Jennifer J. Lentz. (2023) Verification of Estimated Output Signal-to-Noise Ratios From a Phase Inversion Technique Using a Simulated Hearing Aid. American Journal of Audiology 32:1, pages 197-209.
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Ilja Reinten, Inge de Ronde-Brons, Rolph Houben & Wouter Dreschler. (2023) Individual Listener Preference for Strength of Single-Microphone Noise-Reduction; Trade-off Between Noise Tolerance and Signal Distortion Tolerance. Trends in Hearing 27.
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Megan Barnett, Alisha L. Jones & Erin Westbrook. (2021) Acceptable Noise Levels Determined by Traditional and Self-Assessed Methods. Journal of the American Academy of Audiology 32:01, pages 003-009.
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Hendrik Husstedt, Jannine Kreyenhagen, Laura Langhof, Steffen Kreikemeier, Florian Denk, Simone Wollermann & Marlitt Frenz. (2021) Using the phase inversion method and loudness comparisons for the evaluation of noise reduction algorithms in hearing aids. Acta Acustica 5, pages 41.
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Christopher F. Hauth, Simon C. Berning, Birger Kollmeier & Thomas Brand. (2020) Modeling Binaural Unmasking of Speech Using a Blind Binaural Processing Stage. Trends in Hearing 24, pages 233121652097563.
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Tobias May, Borys Kowalewski & Torsten Dau. 2020. The Technology of Binaural Understanding. The Technology of Binaural Understanding 763 799 .
P. F. Khaleelur Rahiman, V. S. Jayanthi & A. N. Jayanthi. (2018) RETRACTED ARTICLE: Deep convolutional neural network-based speech enhancement to improve speech intelligibility and quality for hearing-impaired listeners. Medical & Biological Engineering & Computing 57:3, pages 757-757.
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Borys Kowalewski, Tobias May, Michal Fereczkowski, Johannes Zaar, Olaf Strelcyk, Ewen N. MacDonald & Torsten Dau. (2018) Effects of Fast-Acting Hearing-Aid Compression on Audibility, Forward Masking and Speech Perception. Effects of Fast-Acting Hearing-Aid Compression on Audibility, Forward Masking and Speech Perception.
Tobias May, Borys Kowalewski & Torsten Dau. (2018) Signal-to-Noise-Ratio-Aware Dynamic Range Compression in Hearing Aids. Trends in Hearing 22, pages 233121651879090.
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Lena L. N. Wong, Yuan Chen, Qianran Wang & Volker Kuehnel. (2018) Efficacy of a Hearing Aid Noise Reduction Function. Trends in Hearing 22, pages 233121651878283.
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Dorothea WendtRenskje K. HietkampThomas Lunner. (2017) Impact of Noise and Noise Reduction on Processing Effort: A Pupillometry Study. Ear & Hearing 38:6, pages 690-700.
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Melanie Krueger, Michael Schulte, Melanie A. Zokoll, Kirsten C. Wagener, Markus Meis, Thomas Brand & Inga Holube. (2017) Relation Between Listening Effort and Speech Intelligibility in Noise. American Journal of Audiology 26:3S, pages 378-392.
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Karrie L. Recker & Christophe Micheyl. (2017) Speech Intelligibility as a Cue for Acceptable Noise Levels. Ear & Hearing 38:4, pages 465-474.
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Jessica J. M. Monaghan, Tobias Goehring, Xin Yang, Federico Bolner, Shangqiguo Wang, Matthew C. M. Wright & Stefan Bleeck. (2017) Auditory inspired machine learning techniques can improve speech intelligibility and quality for hearing-impaired listeners. The Journal of the Acoustical Society of America 141:3, pages 1985-1998.
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Anne Schlueter, Ulrike Lemke, Birger Kollmeier & Inga Holube. (2016) Normal and Time-Compressed Speech. Trends in Hearing 20, pages 233121651666988.
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Tobias Neher & Kirsten C. Wagener. (2016) Investigating Differences in Preferred Noise Reduction Strength Among Hearing Aid Users. Trends in Hearing 20, pages 233121651665579.
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Christoph Völker, Anna Warzybok & Stephan M. A. Ernst. (2015) Comparing Binaural Pre-processing Strategies III. Trends in Hearing 19, pages 233121651561860.
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Anne Schlueter, Thomas Brand, Ulrike Lemke, Stefan Nitzschner, Birger Kollmeier & Inga Holube. (2015) Speech perception at positive signal-to-noise ratios using adaptive adjustment of time compression. The Journal of the Acoustical Society of America 138:5, pages 3320-3331.
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Dorothea Wendt, Thomas Brand & Birger Kollmeier. (2014) An Eye-Tracking Paradigm for Analyzing the Processing Time of Sentences with Different Linguistic Complexities. PLoS ONE 9:6, pages e100186.
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Anne Schlueter, Ulrike Lemke, Birger Kollmeier & Inga Holube. (2014) Intelligibility of time-compressed speech: The effect of uniform versus non-uniform time-compression algorithms. The Journal of the Acoustical Society of America 135:3, pages 1541-1555.
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