spectral transition
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2021 ◽  
Vol 104 (17) ◽  
Author(s):  
Zhen-Hua Wang ◽  
Fuming Xu ◽  
Lin Li ◽  
Dong-Hui Xu ◽  
Bin Wang

2021 ◽  
pp. 139028
Author(s):  
Zhi Qin ◽  
Tianrui Bai ◽  
Linhua Liu
Keyword(s):  

2018 ◽  
Vol 483 (1) ◽  
pp. L144-L148 ◽  
Author(s):  
Sergey S Tsygankov ◽  
Alicia Rouco Escorial ◽  
Valery F Suleimanov ◽  
Alexander A Mushtukov ◽  
Victor Doroshenko ◽  
...  
Keyword(s):  
X Ray ◽  

2017 ◽  
Vol 10 (1) ◽  
pp. 114-119
Author(s):  
K Geetha ◽  
R Vadivel

Process of identifying the end points of the acoustic units of the speech signal is called speech segmentation. Speech recognition systems can be designed using sub-word unit like phoneme. A Phoneme is the smallest unit of the language. It is context dependent and tedious to find the boundary. Automated phoneme segmentation is carried in researches using Short term Energy, Convex hull, Formant, Spectral Transition Measure(STM), Group Delay Functions, Bayesian Information Criterion, etc. In this research work, STM is used to find the phoneme boundary of Tamil speech utterances. Tamil spoken word dataset was prepared with 30 words uttered by 4 native speakers with a high quality microphone. The performance of the segmentation is analysed and results are presented.


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