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Machine learning for stuttering identification: Review, challenges and future directions

  • Published:2022-12 Issue: Volume:514 Page:385-402
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Sheikh Shakeel A.,Sahidullah Md,Hirsch Fabrice,Ouni Slim

Funder

Agence Nationale de la Recherche

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference143 articles.

1. Stuttering: An Integrated Approach to its Nature and Treatment;Guitar,2013

2. Motor Speech Disorders Substrates, Differential Diagnosis, and Management;Duffy;Elsevier Health Sciences,2019

3. Fluency bank: A new resource for fluency research and practice;Ratner;Journal of Fluency Disorders,2018

4. Stuttering and Cluttering: Frameworks for Understanding and Treatment;Ward,2008

5. Speech Language Pathology-Stuttering;Kehoe;Kiambo Ridge,2006

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1. Enhancing Stuttering Detection: A Syllable-Level Stutter Dataset;2024 International Conference on Signal Processing and Communications (SPCOM);2024-07-01

2. Aprendizado de máquina no apoio à transcrição e classificação da fala gaguejada: uma revisão sistemática da literatura;Anais do XXIV Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS 2024);2024-06-25

3. A Machine Learning-Enhanced IoT Wearable Device for Monitoring and Providing Feedback on Stuttering;2024 3rd International Conference on Computational Modelling, Simulation and Optimization (ICCMSO);2024-06-14

4. Comparison of performance of automatic recognizers for stutters in speech trained with event or interval markers;Frontiers in Psychology;2024-02-27

5. Towards Inclusive Voice User Interfaces: A Systematic Review of Voice Technology Usability for Users with Communication Disabilities;Communications in Computer and Information Science;2024
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