Results 111 to 120 of about 460,856 (296)

TDNN achitecture with efficient channel attention and improved residual blocks for accurate speaker recognition

Scientific Reports
In recent years, with the advancement of deep learning, Convolutional Neural Networks (CNNs) have been widely applied in speaker recognition, making CNN-based speaker embedding learning the predominant method for speaker verification.
Wenzao Li, Sai Yao, Bing Wan, Linsong Xiao, Chengyu Hou, Yanchuan Zhong, Wengang Zhou   +6 more
doaj   +1 more source

Unified Hypersphere Embedding for Speaker Recognition

CoRR, 2018
Incremental improvements in accuracy of Convolutional Neural Networks are usually achieved through use of deeper and more complex models trained on larger datasets. However, enlarging dataset and models increases the computation and storage costs and cannot be done indefinitely.
Mahdi Hajibabaei, Dengxin Dai
openaire   +3 more sources

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

UC Food Waste: A Multimodal Robotic Perception Dataset for Robust Contaminant Detection in Complex Biowaste Scenes

Advanced Robotics Research, EarlyView.
A balanced multimodal food‐waste dataset and a novel Split Spatial‐Spectral Attention fusion framework are presented for robotic contaminant detection. Separate processing of RGB, thermal, and multispectral inputs preserves subtle material signatures before feature integration, reducing modality interference and improving classification and ...
Matthew Vestal, James Ireland, David Hinwood, Xing Wang, Min Wang, Damith Herath   +5 more
wiley   +1 more source

Graph Learning Based Speaker Independent Speech Emotion Recognition

Advances in Electrical and Computer Engineering, 2014
In this paper, the algorithm based on graph learning and graph embedding framework, Speaker-Penalty Graph Learning (SPGL), is proposed in the research of speech emotion recognition to solve the problems caused by different speakers.
XU, X., HUANG, C., WU, C., WANG, Q., ZHAO, L.   +4 more
doaj   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Improved Convolutional Neural Network–Time-Delay Neural Network Structure with Repeated Feature Fusions for Speaker Verification

Applied Sciences
The development of deep learning greatly promotes the progress of speaker verification (SV). Studies show that both convolutional neural networks (CNNs) and dilated time-delay neural networks (TDNNs) achieve advanced performance in text-independent SV ...
Miaomiao Gao, Xiaojuan Zhang
doaj   +1 more source

Deep speaker representation learning in speaker verification

, 2022
Speaker verification (SV) is the process of verifying whether an utterance belongs to the claimed speaker, based on some reference utterances. Learning effective and discriminative speaker embeddings is a central theme in the speaker verification task ...
Zhu, Yingke
core  

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Persona-ASR: Bilingual Target-Speaker Speech Recognition for Kazakh–English Overlapping Speech

Machine Learning and Knowledge Extraction
Target-speaker automatic speech recognition (TS-ASR) enables transcription of a specific speaker in multi-talker environments, yet remains largely unexplored for multilingual, low-resource languages.
Rakhat Meiramov, Tomiris Rakhimzhanova, Adil Taibassarov, Zhanat Makhataeva, Huseyin Atakan Varol   +4 more
doaj   +1 more source