[PDF][PDF] Explore wav2vec 2.0 for Mispronunciation Detection.

X Xu, Y Kang, S Cao, B Lin, L Ma - Interspeech, 2021 - isca-archive.org
This paper presents an initial attempt to use self-supervised learning for Mispronunciaiton
Detection. Unlike existing methods that use speech recognition corpus to train models, we …

Automatic pronunciation assessment using self-supervised speech representation learning

E Kim, JJ Jeon, H Seo, H Kim - arXiv preprint arXiv:2204.03863, 2022 - arxiv.org
Self-supervised learning (SSL) approaches such as wav2vec 2.0 and HuBERT models have
shown promising results in various downstream tasks in the speech community. In particular …

[HTML][HTML] Computer-assisted pronunciation training—Speech synthesis is almost all you need

D Korzekwa, J Lorenzo-Trueba, T Drugman… - Speech …, 2022 - Elsevier
The research community has long studied computer-assisted pronunciation training (CAPT)
methods in non-native speech. Researchers focused on studying various model …

3m: An effective multi-view, multi-granularity, and multi-aspect modeling approach to english pronunciation assessment

FA Chao, TH Lo, TI Wu, YT Sung… - 2022 Asia-Pacific Signal …, 2022 - ieeexplore.ieee.org
As an indispensable ingredient of computer-assisted pronunciation training (CAPT),
automatic pronunciation assessment (APA) plays a pivotal role in aiding self-directed …

[PDF][PDF] Transformer Based End-to-End Mispronunciation Detection and Diagnosis.

M Wu, K Li, WK Leung, H Meng - Interspeech, 2021 - se.cuhk.edu.hk
This paper introduces two Transformer-based architectures for Mispronunciation Detection
and Diagnosis (MDD). The first Transformer architecture (T-1) is a standard setup with an …

An end-to-end mispronunciation detection system for L2 English speech leveraging novel anti-phone modeling

BC Yan, MC Wu, HT Hung, B Chen - arXiv preprint arXiv:2005.11950, 2020 - arxiv.org
Mispronunciation detection and diagnosis (MDD) is a core component of computer-assisted
pronunciation training (CAPT). Most of the existing MDD approaches focus on dealing with …

[PDF][PDF] Deep Feature Transfer Learning for Automatic Pronunciation Assessment.

B Lin, L Wang - Interspeech, 2021 - isca-archive.org
Automatic pronunciation assessment is commonly developed to evaluate pronunciation
quality of second language (L2) learners. Traditional methods for automatic pronunciation …

Improving mispronunciation detection with wav2vec2-based momentum pseudo-labeling for accentedness and intelligibility assessment

M Yang, K Hirschi, SD Looney, O Kang… - arXiv preprint arXiv …, 2022 - arxiv.org
Current leading mispronunciation detection and diagnosis (MDD) systems achieve
promising performance via end-to-end phoneme recognition. One challenge of such end-to …

Non-autoregressive end-to-end neural modeling for automatic pronunciation error detection

MAH Wadud, M Alatiyyah, MF Mridha - Applied Sciences, 2022 - mdpi.com
A crucial element of computer-assisted pronunciation training systems (CAPT) is the
mispronunciation detection and diagnostic (MDD) technique. The provided transcriptions …

Towards robust mispronunciation detection and diagnosis for L2 English learners with accent-modulating methods

SWF Jiang, BC Yan, TH Lo, FA Chao… - 2021 IEEE Automatic …, 2021 - ieeexplore.ieee.org
With the acceleration of globalization, more and more people are willing or required to learn
second languages (L2). One of the major remaining challenges facing current …