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A Speech-Level–Based Segmented Model to Decode the Dynamic Auditory Attention States in the Competing Speaker Scenes
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In: Front Neurosci (2022)
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The Development of Categorical Perception of Segments and Suprasegments in Mandarin-Speaking Preschoolers
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In: Front Psychol (2021)
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Book Review: Speech Perception, Production and Acquisition: Multidisciplinary Approaches in Chinese Languages
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In: Front Psychol (2021)
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A Review of Speech Perception of Mandarin-Speaking Children With Cochlear Implantation
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In: Front Neurosci (2021)
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Reduced Sensitivity to Between-Category Information but Preserved Categorical Perception of Lexical Tones in Tone Language Speakers With Congenital Amusia
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In: Front Psychol (2020)
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The time course of orthographic and semantic activation in Chinese character recognition: evidence from anERP study ...
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| 9 |
The time course of orthographic and semantic activation in Chinese character recognition: evidence from anERP study ...
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| 10 |
Cantonese Tone Identification in Three Temporal Cues in Quiet, Speech-Shaped Noise and Two-Talker Babble
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| 11 |
Quantitative Assessment of Blood Pressure Measurement Accuracy and Variability from Visual Auscultation Method by Observers without Receiving Medical Training
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Assessing the effect of noise-reduction to the intelligibility of low-pass filtered speech
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| 17 |
Impact of SNR and Gain-Function Over- and Under-estimation on Speech Intelligibility
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Abstract:
Most noise reduction algorithms rely on obtaining reliable estimates of the SNR of each frequency bin. For that reason, much work has been done in analyzing the behavior and performance of SNR estimation algorithms in the context of improving speech quality and reducing speech distortions (e.g., musical noise). Comparatively little work has been reported, however, regarding the analysis and investigation of the effect of errors in SNR estimation on speech intelligibility. It is not known, for instance, whether it is the errors in SNR overestimation, errors in SNR underestimation, or both that are harmful to speech intelligibility. Errors in SNR estimation produce concomitant errors in the computation of the gain (suppression) function, and the impact of gain estimation errors on speech intelligibility is unclear. The present study assesses the effect of SNR estimation errors on gain function estimation via sensitivity analysis. Intelligibility listening studies were conducted to validate the sensitivity analysis. Results indicated that speech intelligibility is severely compromised when SNR and gain over-estimation errors are introduced in spectral components with negative SNR. A theoretical upper bound on the gain function is derived that can be used to constrain the values of the gain function so as to ensure that SNR overestimation errors are minimized. Speech enhancement algorithms that can limit the values of the gain function to fall within this upper bound can improve speech intelligibility.
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Keyword:
Article
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URL: https://doi.org/10.1016/j.specom.2011.09.002
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3224092
http://www.ncbi.nlm.nih.gov/pubmed/22125352
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| 18 |
Contributions of cochlea-scaled entropy and consonant-vowel boundaries to prediction of speech intelligibility in noise
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