Bilingual speaker identification: Chinese and English

2015 ◽  
Vol 22 (1) ◽  
pp. 57-78 ◽  
Author(s):  
Peggy P.K. Mok ◽  
Robert Bo Xu ◽  
Donghui Zuo
2020 ◽  
Vol 63 (7) ◽  
pp. 2245-2254 ◽  
Author(s):  
Jianrong Wang ◽  
Yumeng Zhu ◽  
Yu Chen ◽  
Abdilbar Mamat ◽  
Mei Yu ◽  
...  

Purpose The primary purpose of this study was to explore the audiovisual speech perception strategies.80.23.47 adopted by normal-hearing and deaf people in processing familiar and unfamiliar languages. Our primary hypothesis was that they would adopt different perception strategies due to different sensory experiences at an early age, limitations of the physical device, and the developmental gap of language, and others. Method Thirty normal-hearing adults and 33 prelingually deaf adults participated in the study. They were asked to perform judgment and listening tasks while watching videos of a Uygur–Mandarin bilingual speaker in a familiar language (Standard Chinese) or an unfamiliar language (Modern Uygur) while their eye movements were recorded by eye-tracking technology. Results Task had a slight influence on the distribution of selective attention, whereas subject and language had significant influences. To be specific, the normal-hearing and the d10eaf participants mainly gazed at the speaker's eyes and mouth, respectively, in the experiment; moreover, while the normal-hearing participants had to stare longer at the speaker's mouth when they confronted with the unfamiliar language Modern Uygur, the deaf participant did not change their attention allocation pattern when perceiving the two languages. Conclusions Normal-hearing and deaf adults adopt different audiovisual speech perception strategies: Normal-hearing adults mainly look at the eyes, and deaf adults mainly look at the mouth. Additionally, language and task can also modulate the speech perception strategy.


2012 ◽  
Author(s):  
Chenling Hsieh ◽  
Cheryl Hiscock-Anisman ◽  
Kevin Colwell ◽  
Samantha Florence ◽  
Andrea Sorcinelli ◽  
...  

2020 ◽  
pp. 65-72
Author(s):  
V. V. Savchenko ◽  
A. V. Savchenko

This paper is devoted to the presence of distortions in a speech signal transmitted over a communication channel to a biometric system during voice-based remote identification. We propose to preliminary correct the frequency spectrum of the received signal based on the pre-distortion principle. Taking into account a priori uncertainty, a new information indicator of speech signal distortions and a method for measuring it in conditions of small samples of observations are proposed. An example of fast practical implementation of the method based on a parametric spectral analysis algorithm is considered. Experimental results of our approach are provided for three different versions of communication channel. It is shown that the usage of the proposed method makes it possible to transform the initially distorted speech signal into compliance on the registered voice template by using acceptable information discrimination criterion. It is demonstrated that our approach may be used in existing biometric systems and technologies of speaker identification.


Author(s):  
A. Nagesh

The feature vectors of speaker identification system plays a crucial role in the overall performance of the system. There are many new feature vectors extraction methods based on MFCC, but ultimately we want to maximize the performance of SID system.  The objective of this paper to derive Gammatone Frequency Cepstral Coefficients (GFCC) based a new set of feature vectors using Gaussian Mixer model (GMM) for speaker identification. The MFCC are the default feature vectors for speaker recognition, but they are not very robust at the presence of additive noise. The GFCC features in recent studies have shown very good robustness against noise and acoustic change. The main idea is  GFCC features based on GMM feature extraction is to improve the overall speaker identification performance in low signal to noise ratio (SNR) conditions.


2002 ◽  
Vol 9C (4) ◽  
pp. 459-466
Author(s):  
Dae-Jong Lee ◽  
Geun-Chang Gwak ◽  
Jeong-Ung Yu ◽  
Myeong-Geun Jeon

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