A transfer learning approach to goodness of pronunciation based automatic mispronunciation detection
Goodness of pronunciation (GOP) is the most widely used method for automatic mispronunciation detection. In this paper, a transfer learning approach to GOP based mispronunciation detection when applying maximum F1-score criterion (MFC) training to deep neural network (DNN)-hidden Markov model based...
Saved in:
Main Authors: | Huang, Hao, Xu, Haihua, Hu, Ying, Zhou, Gang |
---|---|
Other Authors: | Temasek Laboratories |
Format: | Article |
Language: | English |
Published: |
2017
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/86625 http://hdl.handle.net/10220/44162 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Automatic speech recognition and chat bot for air traffic control
by: Low, Ashton Kin Yun
Published: (2024) -
A Small vocabulary automatic speech profanity suppression system using Hybrid Hidden Markov Model/ Artificial Neural Network (HMM/ANN) keyword spotting framework
by: Ablaza, Fernando I., Jr., et al.
Published: (2010) -
On-device implementation of an automatic Filipino speech recognition system
by: Ang, Federico M., et al.
Published: (2008) -
Deep Spiking Neural Networks for Large Vocabulary Automatic Speech Recognition
by: Wu, J., et al.
Published: (2021) -
Multi-stage DNN training for automatic recognition of dysarthric speech
by: Yilmaz E., et al.
Published: (2018)