Four experiments investigated the novel issue of learning to accommodate the coarticulated nature of speech. Experiment 1 established a co-articulatory mismatch effect for a set of vowel-consonant (VC) syllables (reaction times were faster for co-articulation matching than for mismatching stimuli). A rhyme judgment training task on words (Experiment 2) or VC stimuli (Experiment 3) with mismatching information was followed by a phoneme monitoring task on a set of VC stimuli; training and test stimuli contained physically identical (same condition) or new (different condition) mismatching coarticulatory information (along with a set containing matching coarticulatory information). A third group received no training. A coarticulatory mismatch effect was found without training but not when the same mismatching tokens were used at training and test. Both word (Experiment 2) and syllable (Experiment 3) training stimuli eliminated the mismatch effect; overall reaction times were somewhat slower when the training stimuli were words. Perceptual learning generalized to new tokens only when the acoustic manifestation of the critical co-articulatory information in the training stimuli was sufficiently large (Experiments 3 and 4). The results are discussed in terms of speech processing and perceptual learning in speech perception.
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http://dx.doi.org/10.1016/j.jml.2009.07.003 | DOI Listing |
iScience
January 2025
Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, 91191 Gif/Yvette, France.
Recent studies showed that humans, regardless of age, education, and culture, can extract the linear trend of a noisy scatterplot. Although this capacity looks sophisticated, it may simply reflect the extraction of the principal trend of the graph, as if the cloud of dots was processed as an oriented object. To test this idea, we trained Guinea baboons to associate arbitrary shapes with the increasing or decreasing trends of noiseless and noisy scatterplots, while varying the number of points, the noise level, and the regression slope.
View Article and Find Full Text PDFDigit Health
January 2025
Independent Researcher, Calgary, Alberta, Canada.
Digital health (DH) and artificial intelligence (AI) in healthcare are rapidly evolving but were addressed synonymously by many healthcare authorities and practitioners. A deep understanding and clarification of these concepts are fundamental and a prerequisite for developing robust frameworks and practical guidelines to ensure the safety, efficacy, and effectiveness of DH solutions and AI-embedded technologies. Categorizing DH into technologies (DHTs) and services (DHSs) enables regulatory, HTA, and reimbursement bodies to develop category-specific frameworks and guidelines for evaluating these solutions effectively.
View Article and Find Full Text PDFTrends Hear
January 2025
Key Laboratory of Noise and Vibration Research, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China.
Wide dynamic range compression (WDRC) and noise reduction both play important roles in hearing aids. WDRC provides level-dependent amplification so that the level of sound produced by the hearing aid falls between the hearing threshold and the highest comfortable level of the listener, while noise reduction reduces ambient noise with the goal of improving intelligibility and listening comfort and reducing effort. In most current hearing aids, noise reduction and WDRC are implemented sequentially, but this may lead to distortion of the amplitude modulation patterns of both the speech and the noise.
View Article and Find Full Text PDFMagn Reson Imaging
January 2025
Department of Medical Imaging, Pingyin people's Hospital, Jinan 250400, China.
Magnetic Resonance Imaging is a cornerstone of medical diagnostics, providing high-quality soft tissue contrast through non-invasive methods. However, MRI technology faces critical limitations in imaging speed and resolution. Prolonged scan times not only increase patient discomfort but also contribute to motion artifacts, further compromising image quality.
View Article and Find Full Text PDFConscious Cogn
January 2025
Humane Technology Lab, Catholic University of Sacred Heart, Milan, Italy; Applied Technology for Neuro-Psychology Lab., Istituto Auxologico Italiano IRCCS, Milan, Italy. Electronic address:
Psychedelic drugs offer valuable insights into consciousness, but disentangling their causal effects on perceptual and high-level cognition is nontrivial. Technological advances in virtual reality (VR) and machine learning have enabled the immersive simulation of visual hallucinations. However, comprehensive experimental data on how these simulated hallucinations affects high-level human cognition is lacking.
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