Sibilant consonants classification comparison with multi‐ and single‐class neural networks-Reference-Cited by-同舟云学术

Sibilant consonants classification comparison with multi‐ and single‐class neural networks

Published:2020-09-09 Issue:6 Volume:37 Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Anjos Ivo¹^ORCID,Marques Nuno¹^ORCID,Grilo Margarida²^ORCID,Guimarães Isabel²³^ORCID,Magalhães João¹^ORCID,Cavaco Sofia¹^ORCID

Affiliation:

1. NOVA LINCS, Department of Computer Science, Faculdade de Ciências e Tecnologia Universidade NOVA de Lisboa Caparica Portugal

2. Escola Superior de Saúde do Alcoitão Alcabideche Portugal

3. Clinical Pharmacological Unit, Instituto de Medicina Molecular, Faculty of Medicine, Universidade de Lisboa Lisboa Portugal

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12620

Reference36 articles.

1. Amodei D. Ananthanarayanan S. Anubhai R. Bai J. Battenberg E. Case C. … Zhenyao Z. et al. (2016). Deep speech 2: End‐to‐end speech recognition in English and Mandarin.Proceedings of the 33rd International Conference on Machine Learning 48 173–182. PMLR.

2. A Serious Mobile Game with Visual Feedback for Training Sibilant Consonants

3. Trial of intensive compared with weekly speech therapy in preschool children.

4. Arabic Speech Pathology Therapy Computer Aided System

5. Intensity of Aphasia Therapy, Impact on Recovery

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Time series forecasting based on a novel ensemble‐based network and variational mode decomposition;Expert Systems;2023-04-27

2. A hierarchical automatic phoneme recognition model forHindi‐Devanagariconsonants using machine learning technique;Expert Systems;2023-03-16

3. Effect of vocal tract dynamics on neural network‐based speech recognition: A Bengali language‐based study;Expert Systems;2022-07-20

4. Noise-based acoustic features of Polish retroflex fricatives in children with normal pronunciation and speech disorder;Journal of Phonetics;2022-05

5. Progress of machine learning based automatic phoneme recognition and its prospect;Speech Communication;2021-12