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Synapse
July 20, 2025

Automatic Speech Recognition for Children: A Systematic Review of Models, Toolkits, and Adaptations

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Authors

RPRaul Benites ParadedaKFKarine Bezerra FurtadoGMGiulia de Oliveira Moscoso

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Overview

Systematic review uncovers effective ASR models for children's speech, highlighting educational adaptations.

Key Points

  • Automatic speech recognition (ASR) can enhance language learning among children, particularly in challenging environments.
  • The review analyzed 16 articles published between 2019 and 2024, focusing on ASR models relevant to children's speech.
  • Deep neural networks and adversarial learning models were identified as the most effective approaches for ASR in children.
  • Challenges such as data scarcity and the need for adaptation to linguistic diversity highlight significant barriers in ASR implementation.

Cite This Study

Paradeda et al. (2025) studied this question.

synapsesocial.com/papers/68af4cebad7bf08b1ead6cfdhttps://doi.org/10.5753/wei.2025.7081
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