Results 51 to 60 of about 76,886 (181)
Soft Active Electromyography Interface for Machine Learning‐Enabled Silent Speech Recognition
Advanced Intelligent Systems, EarlyView.A soft, hand‐worn electromyography interface enables intent‐driven silent speech recognition without continuous facial attachment. The device integrates liquid‐metal interconnects, a transparent flexible circuit, and elastomer encapsulation with a fingertip electrode that contacts perioral muscles only on demand.
Yuta Kurotaki +8 more
wiley +1 more source
Bidirectional Representations for Low-Resource Spoken Language Understanding
Applied Sciences, 2023 Speech representation models lack the ability to efficiently store semantic information and require fine tuning to deliver decent performance. In this research, we introduce a transformer encoder–decoder framework with a multiobjective training strategy,
Quentin Meeus +2 more
doaj +1 more source
Information Dynamics and Learning in Complex Adaptive Systems: Toward a Transdisciplinary Framework
Systems Research and Behavioral Science, Volume 43, Issue 4, Page 1344-1363, July/August 2026.ABSTRACT This article develops a framework for understanding learning and adaptation in complex adaptive systems. Drawing from neuroscience, systems theory, information theory and quantum field theory, it examines how information processing, plasticity and systemic coherence emerge from distributed, nonlinear and feedback‐driven interactions. It argues
Anderson de Souza Sant'Anna
wiley +1 more source
Biomimetic Intelligence and Robotics, 2023 Digital display instrument identification is a crucial approach for automating the collection of digital display data. In this study, we propose a digital display area detection CTPNpro algorithm to address the problem of recognizing multiclass digital ...
Xuanzhang Wen +5 more
doaj +1 more source
On the Proper Treatment of Dynamics in Cognitive Science
Topics in Cognitive Science, Volume 18, Issue 3, July 2026.Abstract This essay examines the relevance of dynamical ideas for cognitive science. On its own, the mere mathematical idea of a dynamical system is too weak to serve as a scientific theory of anything, and dynamical approaches within cognitive science are too rich and varied to be subsumed under a single “dynamical hypothesis.” Instead, after first ...
Randall D. Beer
wiley +1 more source
Inter‐Model Feature Fusion for Robust Low‐Resource Speech Recognition
Applied AI Letters, Volume 7, Issue 2, June 2026.Our Self‐Supervised Feature Fusion (SSF‐FT) method enhances low‐resource speech recognition by adaptively combining features from self‐supervised models trained with Contrastive, Predictive, and Reconstruction objectives. This attention‐weighted ensemble delivers robust performance, particularly in acoustically challenging conditions, extending current
Ussen Kimanuka +2 more
wiley +1 more source
A deep neural network-based automatic mispronunciation detection in Bengali accented English speech
Discover ComputingLearning a second language, especially English, became necessary as globalisation started. One crucial component of language learning resources is computer-assisted pronunciation training, or CAPT.
Puja Bharati +5 more
doaj +1 more source
Attention-based CNN-ConvLSTM for Handwritten Arabic Word Extraction
ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2022 Word extraction is one of the most critical steps in handwritten recognition systems. It is challenging for many reasons, such as the variability of handwritten writing styles, touching and overlapping characters, skewness problems, diacritics ...
takwa Ben Aicha, Afef Kacem Echi
doaj +1 more source
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
wiley +1 more source
Order-Preserving Abstractive Summarization for Spoken Content Based on Connectionist Temporal Classification [PDF]
Interspeech 2017, 2017 Connectionist temporal classification (CTC) is a powerful approach for sequence-to-sequence learning, and has been popularly used in speech recognition. The central ideas of CTC include adding a label "blank" during training. With this mechanism, CTC eliminates the need of segment alignment, and hence has been applied to various sequence-to-sequence ...
Bo-Ru Lu +4 more
openaire +2 more sources