EEG driving fatigue detection based on log-Mel spectrogram and convolutional recurrent neural networks [PDF]
Frontiers in Neuroscience, 2023 Driver fatigue detection is one of the essential tools to reduce accidents and improve traffic safety. Its main challenge lies in the problem of how to identify the driver's fatigue state accurately.
Dongrui Gao +4 more
doaj +2 more sources
Estimation of Elbow Wall Thinning Using Ensemble-Averaged Mel-Spectrogram with ResNet-like Architecture [PDF]
Sensors, 2022 An elbow wall thinning diagnosis method by highlighting the stationary characteristics of the operating loop is proposed. The accelerations of curved pipe surfaces were measured in a closed test loop operating at a constant pump rpm, combined with curved
Jonghwan Kim +3 more
doaj +2 more sources
Newborns' Language Discrimination May Not Reflect Sensitivity to Speech Rhythm: Evidence From Computational Modeling. [PDF]
Dev SciABSTRACT Human newborns are able to discriminate between certain languages but not others. This ability has long been attributed to sensitivity to rhythm—the temporal regularities in speech of different languages. Here, we demonstrate through a series of computational simulations that this discrimination behavior can be achieved using no temporal ...
Famularo RL +3 more
europepmc +2 more sources
Acoustic Signatures of Hive: Detecting Queen Bee Absence Through Machine Learning of Short Audio Segments [PDF]
InsectsHoneybee population decline poses a serious threat to global biodiversity and agricultural productivity, underscoring the need for continuous and non-invasive hive monitoring solutions.
Pablo Ormeño-Arriagada +4 more
doaj +2 more sources
Mel-Weighted Single Frequency Filtering Spectrogram for Dialect Identification
IEEE Access, 2020 In this study, we propose Mel-weighted single frequency filtering (SFF) spectrograms for dialect identification. The spectrum derived using SFF has high spectral resolution for harmonics and resonances while simultaneously maintaining good time ...
Rashmi Kethireddy +2 more
exaly +3 more sources
A Machine Learning Approach to Voice-Based Parkinson Disease Screening Using Multiview Spectrogram and Speech Recognition Features: Diagnostic Study [PDF]
JMIR Medical InformaticsBackgroundParkinson disease frequently manifests early vocal impairment, motivating the development of noninvasive and scalable digital screening tools.
Arifa Zahir +5 more
doaj +2 more sources
Cough Recognition Based on Mel-Spectrogram and Convolutional Neural Network [PDF]
Frontiers in Robotics and AI, 2021 Quan Zhou, Jianhua Shan, Wenlong Ding
exaly +2 more sources
IEEE Access, 2023 Speech emotion recognition aims to automatically identify and classify emotions from speech signals. It plays a crucial role in various applications such as human-computer interaction, affective computing, and social robotics. Over the years, researchers
Kah Liang Ong +2 more
exaly +3 more sources
Snoring sound classification in patients with cerebrovascular stenosis based on an improved ConvNeXt model [PDF]
Frontiers in PhysiologyIntroductionSnoring is a common symptom of Obstructive Sleep Apnea (OSA) and has also been associated with an elevated risk of cerebrovascular disease. However, existing snoring detection studies predominantly focus on individuals with Obstructive Sleep ...
Caijian Hua +4 more
doaj +2 more sources
Applied Sciences, 2022 The performance of speaker recognition systems is very well on the datasets without noise and mismatch. However, the performance gets degraded with the environmental noises, channel variation, physical and behavioral changes in speaker.
Wondimu Lambamo +2 more
doaj +1 more source