Mispronunciation Detection Using Deep Convolutional Neural Network Features and Transfer Learning-Based Model for Arabic Phonemes

Mispronunciation Detection Using Deep Convolutional Neural Network Features and Transfer Learning-Based Model for Arabic Phonemes

Computer-assisted language learning (CALL) systems provide an automated framework to identify mispronunciation and give useful feedback. Traditionally, handcrafted acoustic-phonetic features are used to detect mispronunciation. From this line of research, this paper investigates the use of the deep...

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Bibliographic Details
Main Authors: Faria Nazir, Muhammad Nadeem Majeed, Mustansar Ali Ghazanfar, Muazzam Maqsood
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Mispronunciation detection
deep convolutional neural network
computer-assisted language learning
transfer learning
Online Access:https://ieeexplore.ieee.org/document/8695703/

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