DocumentCode :
3284031
Title :
A Novel Clustering Algorithm for Mining Speech Data Using Baysian Network-Based Mutliple Model
Author :
Zhao, Feng ; Wu, Delong ; Yuan, Pingpeng ; Jin, Hai
Author_Institution :
Services Comput. Technol. & Syst. Lab., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2009
fDate :
16-17 May 2009
Firstpage :
617
Lastpage :
620
Abstract :
With the development of speech recognition, speech data mining becomes a hot topic in fields of data mining and natural language processing. In this paper, a novel clustering algorithm is presented to describe how to do semantic mining and how to understand the developing trend of event implied in speech sequence. At first, the speech sequences are extracted into a Bayesian network presenting the relationship between different speech elements. Then, we utilize a 3-dimensional space and sequence cluster techniques to excavate implied information from speech. Considering speech data features, we improve traditional distance-based clustering algorithm to get semantic information and enhance performance. The experimental results show that our algorithm is correct and effective.
Keywords :
data mining; natural language processing; pattern clustering; speech recognition; 3D space; Bayesian network-based multiple model; distance-based clustering algorithm; natural language processing; semantic mining; sequence cluster technique; speech data mining; speech recognition; speech sequence extraction; Association rules; Circuits; Clustering algorithms; Data mining; Humans; Natural language processing; Speech analysis; Speech enhancement; Speech processing; Speech recognition; Baysian Network; Frequent sequence; Sequence cluster; Speech data mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits, Communications and Systems, 2009. PACCS '09. Pacific-Asia Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3614-9
Type :
conf
DOI :
10.1109/PACCS.2009.72
Filename :
5232018
Link To Document :
بازگشت