Results 41 to 50 of about 2,773 (174)

A Unified Approach to Voice Classification: Leveraging Spectrograms, Mel Spectrograms, and Statistical Features

IEEE Access
This study presents a multi-input neural network architecture for voice classification that integrates two parallel convolutional neural networks (CNNs) for spectrogram and Mel spectrogram images, along with a fully connected dense network for six handpicked numerical statistical features from time domain signal.
Muhammad Talha, Huma Ghafoor, Seung Yeob Nam   +2 more
openaire   +2 more sources

Passive Acoustic Identification of Social Groups in the Hainan Gibbon

Remote Sensing in Ecology and Conservation, EarlyView.
Passive acoustic monitoring offers a non‐invasive means of assessing visually hard‐to‐survey wildlife species with distinctive vocalizations. We evaluated whether deep learning can identify Hainan gibbon (Nomascus hainanus) social groups from their calls.
Emmanuel Kabuga, Emmanuel Dufourq, Nonhlanhla L. Luphade, Samuel T. Turvey, Heidi Ma, Susan M. Cheyne, Hui Liu, Jessica V. Bryant, Qing Chen, Wenyong Li, Zhiwei Liu, Zhaoli Zhou, Stefan Britz, Bubacarr Bah, Ian Durbach   +14 more
wiley   +1 more source

A voiceprint pattern recognition method of smoothing reactor based on CNN

Zhejiang dianli, 2023
In order to accurately identify the operating condition of the smoothing reactor， a deep learning method based on CNN （convolutional neural network） is introduced.
HU Jingen, SHI Minglei, JIAO Chenhua, SHEN Zhengyuan   +3 more
doaj   +1 more source

Widespread Bomb Fishing in Indo‐Pacific Archipelago Revealed Through Machine Learning Accelerated Passive Acoustic Monitoring

Remote Sensing in Ecology and Conservation, EarlyView.
AI‐accelerated passive acoustic monitoring reveals extensive bomb fishing within the Spermonde Archipelago, with annual incidents numbering in the thousands. ABSTRACT Bomb fishing is recognised as the most destructive fishing practice that can be performed in our oceans.
Ben Williams, Mars Coral Restoration Project Monitoring Team, Aimee du Luart, Sonny Burniston, Tries B. Razak, Timothy A. C. Lamont, David J. Smith, Jamaluddin Jompa, David Curnick, Kate E. Jones   +9 more
wiley   +1 more source

Few Annotations, High Accuracy: Transfer Learning and Data Augmentation Improve Passive Acoustic Monitoring of the Vulnerable African Manatee

Remote Sensing in Ecology and Conservation, EarlyView.
Can deep learning reliably detect a threatened species in passive acoustic monitoring with few annotations? Across 52 sites and 600 recording days, we compared two deep learning recognizers with the traditional machine learning Kaleidoscope for detecting African manatee vocalizations.
Lucas Dubus, Auguste Verdier, Nina Giotto, Grace Mbemba, Gabriel Michelin, Baptiste Mulot, Stéphanie Manel, David Mouillot   +7 more
wiley   +1 more source

Is GAN Necessary for Mel-Spectrogram-Based Neural Vocoder?

IEEE Signal Processing Letters
Accepted by IEEE Signal Processing ...
Hui-Peng Du, Yang Ai, Rui-Chen Zheng, Ye-Xin Lu, Zhen-Hua Ling   +4 more
openaire   +3 more sources

Progress in Explosion Mechanisms and Prevention Technologies for Direct Chill Casting Aluminum Melt Upon Water Contact: A Review

Safety Science and Technology, EarlyView.
Molten aluminum–water explosion triggered by leakage remains the core unresolved safety hazard hindering safe production in aluminum direct chill casting. This review summarizes its explosion mechanism, key influencing factors, prevention technologies, existing gaps, and prospects of intelligent multi‐technology integrated explosion‐proof systems ...
Min Wang, Kang Yang, Jiang Dong, Lidong Xing, Bing Chen, Changke Chen   +5 more
wiley   +1 more source

Music Genre Classification Using Dual-Branch Feature Fusion of Mel-Spectrogram Embeddings and Acoustic Statistical Descriptors

IEEE Access
Music genre classification is a fundamental task in music information retrieval, audio signal processing, recommendation systems, and digital music resource management.
Yuchen Guo
doaj   +1 more source

Artificial Intelligence in Voice Disorders: Current Landscape, Emerging Applications and Future Directions

World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
ABSTRACT Objective To provide a comprehensive review of the current landscape of artificial intelligence (AI) applications in voice disorder, with emphasis on emerging applications, limitations, and future directions for clinical integration. Methods Literature review.
Rachel B. Kutler, Anaïs Rameau
wiley   +1 more source

Non-Intrusive Air Traffic Control Speech Quality Assessment with ResNet-BiLSTM

Applied Sciences, 2023
In the current field of air traffic control speech, there is a lack of effective objective speech quality evaluation methods. This paper proposes a new network framework based on ResNet–BiLSTM to address this issue.
Yuezhou Wu, Guimin Li, Qiang Fu
doaj   +1 more source