Results 81 to 90 of about 7,229,432 (222)

Snoring Sound Recognition Using Multi-Channel Spectrograms

Archives of Acoustics
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a common and high-risk sleep-related breathing disorder. Snoring detection is a simple and non-invasive method. In many studies, the feature maps are obtained by applying a short-time Fourier transform
Ziqiang YE, Jianxin PENG, Xiaowen ZHANG, Lijuan SONG   +3 more
doaj   +1 more source

Recognizing Semi-Natural and Spontaneous Speech Emotions Using Deep Neural Networks

IEEE Access, 2022
We needed to find deep emotional features to identify emotions from audio signals. Identifying emotions in spontaneous speech is a novel and challenging subject of research.
Ammar Amjad, Lal Khan, Noman Ashraf, Muhammad Bilal Mahmood, Hsien-Tsung Chang   +4 more
doaj   +1 more source

Acoustic Features, Parental Perception and Developmental Correlations of Crying in Preterm Infants: A Systematic Review and Meta‐Analysis

Infancy, Volume 31, Issue 4, July/August 2026.
ABSTRACT Infants born preterm present a higher likelihood of differences in social and emotional communication. Crying, as the earliest form of human communication, may provide valuable information about early neurodevelopment. Understanding its acoustic characteristics and how caregivers perceive it can help identify early patterns linked to ...
Giselle V. Mannarino, Suhail R. Ali‐Briceño, Álvaro Bejarano‐Martín, María Magán‐Maganto, Ricardo Canal‐Bedia   +4 more
wiley   +1 more source

Graph Embedding With Mel-Spectrograms for Underwater Acoustic Target Recognition

IEEE Journal of Oceanic Engineering
Underwater acoustic target recognition (UATR) is extremely challenging due to the complexity of ship-radiated noise and the variability of ocean environments. Although deep learning (DL) approaches have achieved promising results, most existing models implicitly assume that underwater acoustic data lie in a Euclidean space. This assumption, however, is
Sheng Feng, Shuqing Ma, Xiaoqian Zhu
openaire   +2 more sources

Comparison results on the mel-spectrogram dataset.

Comparison results on the mel-spectrogram dataset.
Thanh-Cong Truong (18452213), Quoc Bao Diep (18452207), Hong Yen Phan (18452210)   +2 more
core   +1 more source

Drill Fault Diagnosis Based on the Scalogram and Mel Spectrogram of Sound Signals Using Artificial Intelligence

, 2020
In industry, the ability to detect damage or abnormal functioning in machinery is very important. However, manual detection of machine fault sound is economically inefficient and labor-intensive.
Lundgren, Jan, Tran, Thanh,, Tran, Thanh, Lundgren, Jan,   +3 more
core   +1 more source

Exploring the Impact of Image-Based Audio Representations in Classification Tasks Using Vision Transformers and Explainable AI Techniques

Information
An important hurdle in medical diagnostics is the high-quality and interpretable classification of audio signals. In this study, we present an image-based representation of infant crying audio files to predict abnormal infant cries using a vision ...
Sari Masri, Ahmad Hasasneh, Mohammad Tami, Chakib Tadj   +3 more
doaj   +1 more source

Advancing Marine Bioacoustics With Deep Generative Models: A Hybrid Augmentation Strategy for Southern Resident Killer Whale Detection

Marine Mammal Science, Volume 42, Issue 3, July 2026.
ABSTRACT Automated detection and classification of marine mammal vocalizations is critical for conservation and management efforts but is hindered by limited annotated datasets and the acoustic complexity of real‐world marine environments. Data augmentation has proven to be an effective strategy to address this limitation by increasing dataset ...
Bruno Padovese, Fabio Frazao, Michael Dowd, Ruth Joy   +3 more
wiley   +1 more source

Adaptive Acoustic Monitoring for Endangered Cook Inlet Beluga Whales in Complex Soundscapes

Marine Mammal Science, Volume 42, Issue 3, July 2026.
ABSTRACT Effective conservation of the endangered Cook Inlet beluga whale (Delphinapterus leucas) requires comprehensive spatiotemporal data, yet monitoring efforts remain spatially biased, underrepresenting important southern habitats. Passive acoustic monitoring (PAM) provides the necessary broad‐scale coverage, but its expansion introduces ...
Manuel Castellote, Rahul Dodhia, Daniela Ruiz, Zhongqi Miao, Pablo Arbelaez, Verena Gill, Lori Polasek, Juan M. Lavista Ferres   +7 more
wiley   +1 more source

Speech, spectrogram, mel-spectrogram and mfcc images of used datasets.

Speech, spectrogram, mel-spectrogram and mfcc images of used datasets.
Thanh-Cong Truong (18452213), Quoc Bao Diep (18452207), Hong Yen Phan (18452210)   +2 more
core   +1 more source