Computer-assisted pronunciation training: From pronunciation scoring towards spoken language learning

NF Chen, H Li - 2016 Asia-Pacific Signal and Information …, 2016 - ieeexplore.ieee.org
This paper reviews the research approaches used in computer-assisted pronunciation
training (CAPT), addresses the existing challenges, and discusses emerging trends and …

Mispronunciation detection and diagnosis in l2 english speech using multidistribution deep neural networks

K Li, X Qian, H Meng - IEEE/ACM Transactions on Audio …, 2016 - ieeexplore.ieee.org
This paper investigates the use of multidistribution deep neural networks (DNNs) for
mispronunciation detection and diagnosis (MDD), to circumvent the difficulties encountered …

Automatic Pronunciation Assessment--A Review

YE Kheir, A Ali, SA Chowdhury - arxiv preprint arxiv:2310.13974, 2023 - arxiv.org
Pronunciation assessment and its application in computer-aided pronunciation training
(CAPT) have seen impressive progress in recent years. With the rapid growth in language …

[PDF][PDF] Automatic error detection in pronunciation training: Where we are and where we need to go

SM Witt - International Symposium on automatic detection on …, 2012 - researchgate.net
This paper discusses the state of the art of research in computer assisted pronunciation
teaching as of early 2012. A discussion of all major components contributing to …

End-to-end automatic pronunciation error detection based on improved hybrid ctc/attention architecture

L Zhang, Z Zhao, C Ma, L Shan, H Sun, L Jiang… - Sensors, 2020 - mdpi.com
Advanced automatic pronunciation error detection (APED) algorithms are usually based on
state-of-the-art automatic speech recognition (ASR) techniques. With the development of …

[HTML][HTML] Automatic Speech Recognition and Pronunciation Error Detection of Dutch Non-native Speech: cumulating speech resources in a pluricentric language

X Wei, C Cucchiarini, R van Hout, H Strik - Speech Communication, 2022 - Elsevier
The shortage of large-scale learners' speech corpora and precise manual annotations are
two major challenges for automatic L2 speech recognition and error detection in L2 speech …

A dimensionality reduction-based efficient software fault prediction using Fisher linear discriminant analysis (FLDA)

A Kalsoom, M Maqsood, MA Ghazanfar, F Aadil… - The Journal of …, 2018 - Springer
Software quality is an important factor in the success of software companies. Traditional
software quality assurance techniques face some serious limitations especially in terms of …

Cross-lingual transfer learning of non-native acoustic modeling for pronunciation error detection and diagnosis

R Duan, T Kawahara, M Dantsuji… - IEEE/ACM Transactions …, 2019 - ieeexplore.ieee.org
In computer-assisted pronunciation training (CAPT), the scarcity of large-scale non-native
corpora and human expert annotations are two fundamental challenges to non-native …

[PDF][PDF] Landmark-based automated pronunciation error detection.

SY Yoon, M Hasegawa-Johnson, R Sproat - Interspeech, 2010 - isca-archive.org
We present a pronunciation error detection method for second language learners of English
(L2 learners). The method is a combination of confidence scoring at the phone level and …

[PDF][PDF] New perspectives in teaching pronunciation

MG Busa - 2008 - openstarts.units.it
Computer Assisted Language Learning (CALL) applications are a useful aid for both
language teachers and individual learners. CALL applications offer individualized …