Tone recognition of continuous Mandarin speech based on neural networks

1995 ◽  
Vol 3 (2) ◽  
pp. 146-150 ◽  
Author(s):  
Sim-Horng Chen ◽  
Yih-Ru Wang
Keyword(s):  
Neural Networks ◽  
Tone Recognition

A Mathematical Morphological Processing of Spectrograms for the Tone of Chinese Vowels Recognition

2014 ◽  
Vol 571-572 ◽  
pp. 665-671 ◽  
Author(s):  
Sen Xu ◽  
Xu Zhao ◽  
Cheng Hua Duan ◽  
Xiao Lin Cao ◽  
Hui Yan Li ◽  
...  
Keyword(s):  
Neural Networks ◽  
Speech Recognition ◽  
Emotion Recognition ◽  
Recognition Rate ◽  
Morphological Processing ◽  
Speech Emotion Recognition ◽  
Normal Tone ◽  
Tone Recognition ◽  
Tone Signal ◽  
The Neural Networks

As One of Features from other Languages, the Chinese Tone Changes of Chinese are Mainly Decided by its Vowels, so the Vowel Variation of Chinese Tone Becomes Important in Speech Recognition Research. the Normal Tone Recognition Ways are Always Based on Fundamental Frequency of Signal, which can Not Keep Integrity of Tone Signal. we Bring Forward to a Mathematical Morphological Processing of Spectrograms for the Tone of Chinese Vowels. Firstly, we will have Pretreatment to Recording Good Tone Signal by Using Cooledit Pro Software, and Converted into Spectrograms; Secondly, we will do Smooth and the Normalized Pretreatment to Spectrograms by Mathematical Morphological Processing; Finally, we get Whole Direction Angle Statistics of Tone Signal by Skeletonization way. the Neural Networks Stimulation Shows that the Speech Emotion Recognition Rate can Reach 92.50%.

Probabilistic neurotransmitter release for dynamic synapse neural networks and its application on pure tone recognition

2003 ◽  
Vol 114 (4) ◽  
pp. 2331-2332
Author(s):  
Alireza A. Dibazar ◽  
Hassan H. Namarvar ◽  
Sageev George ◽  
Theodore W. Berger
Keyword(s):  
Neural Networks ◽  
Neurotransmitter Release ◽  
Pure Tone ◽  
Dynamic Synapse ◽  
Tone Recognition

TONE RECOGNITION OF CONTINUOUS THAI SPEECH UNDER TONAL ASSIMILATION AND DECLINATION EFFECTS USING HALF-TONE MODEL

2001 ◽  
Vol 09 (06) ◽  
pp. 815-825 ◽  
Author(s):  
NUTTAKORN THUBTHONG ◽  
BOONSERM KIJSIRIKUL
Keyword(s):  
Neural Networks ◽  
Recognition Rate ◽  
Feedforward Neural Networks ◽  
Training Time ◽  
Tone Recognition ◽  
Context Dependent ◽  
Novel Model

This paper presents a method for continuous Thai tone recognition. One of the main problems in tone recognition is that several interacting factors affect F0realization of tones. In this paper, we focus on the tonal assimilation and declination effects. These effects are compensated by the tone information of neighboring syllables, the F0downdrift and the context-dependent tone model. However, the context-dependent tone model is too large and its training time is very long. To overcome these problems, we propose a novel model called the half-tone model. The experiments, which compare all tone features and all tone models, were simulated by feedforward neural networks. The results show that the proposed tone features increase the recognition rates and the half-tone model outperforms conventional tone models, i.e. context-independent and context-dependent tone models, in terms of recognition rate and speed. The best results are 94.77% and 93.82% for the inside test and outside test, respectively.

A Method for Isolated Thai Tone Recognition Using a Combination of Neural Networks

2002 ◽  
Vol 18 (3) ◽  
pp. 313-335 ◽  
Author(s):  
Nuttakorn Thubthong ◽  
Boonserm Kijsirikul ◽  
Apirath Pusittrakul
Keyword(s):  
Neural Networks ◽  
Tone Recognition
Sign in / Sign up

Export Citation Format

Share Document