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