Results 81 to 90 of about 14,332 (195)

Text-Independent Phone-to-Audio Alignment Leveraging SSL (TIPAA-SSL) Pre-Trained Model Latent Representation and Knowledge Transfer

open access: yesAcoustics
In this paper, we present a novel approach for text-independent phone-to-audio alignment based on phoneme recognition, representation learning and knowledge transfer.
Noé Tits   +2 more
doaj   +1 more source

Variational Connectionist Temporal Classification for Order-Preserving Sequence Modeling

open access: yesICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
5 pages, 3 figures ...
Nan, Zheng   +3 more
openaire   +2 more sources

Audio Tagging With Connectionist Temporal Classification Model Using Sequentially Labelled Data

open access: yes, 2019
Audio tagging aims to predict one or several labels in an audio clip. Many previous works use weakly labelled data (WLD) for audio tagging, where only presence or absence of sound events is known, but the order of sound events is unknown. To use the order information of sound events, we propose sequential labelled data (SLD), where both the presence or
Hou, Yuanbo   +2 more
openaire   +2 more sources

AI in Neurology: Everything, Everywhere, All at Once Part 1: Principles and Practice

open access: yesAnnals of Neurology, Volume 98, Issue 2, Page 211-230, August 2025.
Artificial intelligence (AI) is rapidly transforming healthcare, yet it often remains opaque to clinicians, scientists, and patients alike. This review, part 1 of a 3‐part series, provides neurologists and neuroscientists with a foundational understanding of AI's key concepts, terminology, and applications.
Matthew Rizzo, Jeffrey D. Dawson
wiley   +1 more source

A Connectionist Model of Spatial Knowledge Acquisition in a Virtual Environment [PDF]

open access: yes, 2003
This paper proposes the use of neural networks as a tool for studying navigation within virtual worlds. Results indicate that network learned to predict the next step for a given trajectory, acquiring also basic spatial knowledge in terms of landmarks ...
O'Hare, G.M.P., Reilly, R., Sas, Corina
core  

Prerequisite Relations Annotation Tool: Annotation and analysis of educational relations in texts

open access: yesJournal of the Association for Information Science and Technology, Volume 76, Issue 7, Page 1006-1027, July 2025.
Abstract Relations between terms in texts have long been studied in linguistics and specialized knowledge domains, especially when occurring in educational materials like textbooks, where they play a crucial role in guiding instructional design and learning.
Chiara Alzetta, Ilaria Torre
wiley   +1 more source

Blueprint for a Universal Theory of Learning to Read: The Combinatorial Model

open access: yesReading Research Quarterly, Volume 60, Issue 2, April/May/June 2025.
The Reading Tree. Abstract In this essay, I outline some of the essential ingredients of a universal theory of reading acquisition, one that seeks to highlight commonalities while embracing the global diversity of languages, writing systems, and cultures.
David L. Share
wiley   +1 more source

Speech Recognition for Air Traffic Control Utilizing a Multi-Head State-Space Model and Transfer Learning

open access: yesAerospace
In the present study, a novel end-to-end automatic speech recognition (ASR) framework, namely, ResNeXt-Mssm-CTC, has been developed for air traffic control (ATC) systems.
Haijun Liang, Hanwen Chang, Jianguo Kong
doaj   +1 more source

Dimensions of Neural-symbolic Integration - A Structured Survey

open access: yes, 2005
Research on integrated neural-symbolic systems has made significant progress in the recent past. In particular the understanding of ways to deal with symbolic knowledge within connectionist systems (also called artificial neural networks) has reached a ...
Bader, Sebastian, Hitzler, Pascal
core   +1 more source

On Robustness of the Explanatory Power of Machine Learning Models: Insights From a New Explainable AI Approach Using Sensitivity Analysis

open access: yesWater Resources Research, Volume 61, Issue 3, March 2025.
Abstract Machine learning (ML) is increasingly considered the solution to environmental problems where limited or no physico‐chemical process understanding exists. But in supporting high‐stakes decisions, where the ability to explain possible solutions is key to their acceptability and legitimacy, ML can fall short. Here, we develop a method, rooted in
Banamali Panigrahi   +5 more
wiley   +1 more source

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