Language comprehension in noise can sometimes lead to mishearing, due to the noise disrupting the speech signal. Some of the difficulties in dealing with the noisy signal can be alleviated by drawing on the context - indeed, top-down predictability has shown to facilitate speech comprehension in noise. Previous studies have furthermore shown that strong reliance on the top-down predictions can lead to increased rates of mishearing, especially in older adults, which are attributed to general deficits in cognitive control in older adults. We here propose that the observed mishearing may be a simple consequence of rational language processing in noise. It should not be related to failure on the side of the older comprehenders, but instead would be predicted by rational processing accounts. To test this hypothesis, we extend earlier studies by running an online listening experiment with younger and older adults, carefully controlling the target and direct competitor in our stimuli. We show that mishearing is directly related to the perceptibility of the signal. We furthermore add an analysis of wrong responses, which shows that results are at odds with the idea that participants overly strongly rely on context in this task, as most false answers are indeed close to the speech signal, and not to the semantics of the context.
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http://dx.doi.org/10.3389/fpsyg.2021.679278 | DOI Listing |
Data Brief
February 2025
Department of CSE, Daffodil International University, Bangladesh.
A comprehensive dataset on lemon leaf disease can surely bring a lot of potentials into the development of agricultural research and the improvement of disease management strategies. This dataset was developed from 1354 raw images taken with professional agricultural specialist guidance from July to September 2024 in Charpolisha, Jamalpur, and further enhanced with augmented techniques, adding 9000 images. The augmentation process involves a set of techniques-flipping, rotation, zooming, shifting, adding noise, shearing, and brightening-to increase variety for different lemon leaf condition representations.
View Article and Find Full Text PDFJ Neurosci
January 2025
Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742
When we listen to speech, our brain's neurophysiological responses "track" its acoustic features, but it is less well understood how these auditory responses are enhanced by linguistic content. Here, we recorded magnetoencephalography (MEG) responses while subjects of both sexes listened to four types of continuous-speech-like passages: speech-envelope modulated noise, English-like non-words, scrambled words, and a narrative passage. Temporal response function (TRF) analysis provides strong neural evidence for the emergent features of speech processing in cortex, from acoustics to higher-level linguistics, as incremental steps in neural speech processing.
View Article and Find Full Text PDFPLoS One
January 2025
College of Arts, Anhui Xinhua University, Hefei, China.
To improve the expressiveness and realism of illustration images, the experiment innovatively combines the attention mechanism with the cycle consistency adversarial network and proposes an efficient style transfer method for illustration images. The model comprehensively utilizes the image restoration and style transfer capabilities of the attention mechanism and the cycle consistency adversarial network, and introduces an improved attention module, which can adaptively highlight the key visual elements in the illustration, thereby maintaining artistic integrity during the style transfer process. Through a series of quantitative and qualitative experiments, high-quality style transfer is achieved, especially while retaining the original features of the illustration.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Orofacial Pain and Oral Medicine, Yonsei University College of Dentistry, 50-1, Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
This study aimed to develop an artificial intelligence (AI) model for the screening of degenerative joint disease (DJD) using temporomandibular joint (TMJ) panoramic radiography and joint noise data. A total of 2631 TMJ panoramic images were collected, resulting in a final dataset of 3908 images (2127 normal (N) and 1781 DJD (D)) after excluding indeterminate cases and errors. AI models using GoogleNet were evaluated with six different combinations of image data, clinician-detected crepitus, and patient-reported joint noise.
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
Electronics and Communication Engineering, Rajiv Gandhi University, Rono Hills, Doimukh, ITANAGAR, Itanagar, Arunachal Pradesh, 791112, INDIA.
Accurate detection of cardiac arrhythmias is crucial for preventing premature deaths. The current study employs a dual-stage Discrete Wavelet Transform (DWT) and a median filter to eliminate noise from ECG signals. Subsequently, ECG signals are segmented, and QRS regions are extracted for further preprocessing.
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