Tone error detection of continuous Mandarin speech for L2 learners based on TAM-BLSTM

Yizhi Wu; Tong Guan

doi:10.1117/12.2639121

15 July 2022 Tone error detection of continuous Mandarin speech for L2 learners based on TAM-BLSTM

Yizhi Wu, Tong Guan

Proceedings Volume 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022); 1225816 (2022) https://doi.org/10.1117/12.2639121
Event: International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 2022, Qingdao, China

Abstract

To effectively help second language (L2) Chinese learners to produce tones correctly in computer assisted language learning (CALL), tone recognition of continuous speech is necessary. Because of the complex tone variation in continuous speech, this paper proposed TAM-BLSTM tone recognition model. Firstly, the generation model, target approximation model (TAM) is used to simulate fundamental frequency (f0) from original f0 contour in the unit of prosodic words, and the TAM parameters for each Chinese character are derived. Then BLSTM model with attention mechanism is set up with input feature of the TAM parameters and basic acoustic features, such as statistical f0 parameters, vowel duration, to solve the problem of tone detection of Mandarin continuous speech. Finally, the trained tone detection model is applied to the tone error detection of the L2 learners. The experimental results with Biaobei corpus show that the accuracy of the feature set combined with TAM parameters is 2.3% higher than that of using basic acoustic features alone, and the overall accuracy of ATT-BLSTM network model is higher than that based on ATT-LSTM.

Citation Download Citation

Yizhi Wu and Tong Guan "Tone error detection of continuous Mandarin speech for L2 learners based on TAM-BLSTM", Proc. SPIE 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 1225816 (15 July 2022); https://doi.org/10.1117/12.2639121

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
5 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Acoustics

Error analysis

Feature extraction

Target detection

Performance modeling

Statistical modeling

Solids

Show All Keywords

Keywords/Phrases

Search In:

Publication Years