DocumentCode :
3582852
Title :
Multipitch tracking with continuous correlation feature and hybrid DBNS/HMM model
Author :
Jie Lin ; Gen Zhang ; Bo Fu ; Yujie Hao
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2014
Firstpage :
218
Lastpage :
221
Abstract :
This paper proposed a new approach used for tracking multi-pith within one mixture speech signal. In this method, we employed a novel continuous correlation feature for calculating pitch model. This feature not only represents the harmonicity but also includes the information of spectral continuity, and hence improving the accuracy of the multi-pitch estimate. A DBNs and HMM hybrid model was further utilized to construct pitch models for determining pitch states and search for the best pitch state sequence. The new approach has been evaluated on mixture speech data and the results demonstrated its efficiency.
Keywords :
belief networks; estimation theory; hidden Markov models; speech processing; continuous correlation feature; deep belief network; hidden Markov model; hybrid DBNS-HMM model; mixture speech data; multipitch estimate; multipitch tracking; pitch state sequence; spectral continuity; speech signal; Acoustics; Correlation; Hidden Markov models; Signal processing algorithms; Speech; Speech processing; Vectors; HMM; Pitch detection; deep belief network; multi-pitch tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2014 11th International Computer Conference on
Print_ISBN :
978-1-4799-7207-4
Type :
conf
DOI :
10.1109/ICCWAMTIP.2014.7073394
Filename :
7073394
Link To Document :
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