Results 141 to 150 of about 41,235 (305)
Adaptive Gain Equalizer for Speech Enhancement
, 2002 This report presents a noise reduction method for speech communication where the input signal is divided into a number of subbands that are individually weighted in time domain according to the short time Signal-to-Noise Ratio estimate (SNR) in each ...
Westerlund, Nils +2 more
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New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Mental well‐being is central to adult learner success, yet many adult education institutions lack capacity to provide timely and accessible support. This article examines how artificial intelligence (AI) can strengthen mental health–adjacent supports in adult and continuing higher education, with attention to professional practice and ...
Adam L. McClain, Thomas Wade
wiley +1 more source
Characterization of Deep Learning-Based Speech-Enhancement Techniques in Online Audio Processing Applications. [PDF]
Sensors (Basel), 2023 Rascon C.
europepmc +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi +2 more
wiley +1 more source
, 2010 Traditional speech enhancement methods optimise signal-level\ud criteria such as signal-to-noise ratio, but such approaches are sub-optimal for noise-robust speech recognition.
Kleinschmidt, Tristan +2 more
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Speech enhancement by residual domain constrained optimization
, 2006 A new algorithm for the enhancement of speech corrupted by additive noise is proposed. This algorithm estimates the linear prediction residuals of the clean speech using a constrained optimization criterion.
Jin, Wen, Scordilis, Michael S
core +1 more source
Patch-based domain adversarial training for speech enhancement
Dianxin kexueIn deep learning-based speech enhancement methods, mismatched distributions between training data and test data are often encountered. These mismatches can include differences in speakers, speech content, noise types, and signal-to-noise ratios between ...
WANG Hongtao +3 more
doaj
Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler +20 more
wiley +1 more source
A long state vector Kalman filter for speech enhancement
, 2008 In this paper, we investigate a long state vector Kalman filter for the enhancement of speech that has been corrupted by white and coloured noise. It has been reported in previous studies that a vector Kalman filter achieves better enhancement than the ...
So, Stephen, Paliwal, Kuldip K
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Do non-native listeners benefit from speech modifications designed to promote intelligibility for native listeners? [PDF]
, 2012 Given the increasing use of sound output technologies in cluttered acoustic environments such as transport interchanges, it is of interest to discover ways to modify generated speech which maximise the likelihood of correct message reception, without ...
Wester, Mirjam; id_orcid +3 more
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