Fuzzy clustering approach using data fusion theory and its application to automatic isolated word recognition

Moshiri, B., Eslambolchilar, Parisa ORCID: https://orcid.org/0000-0003-4610-1643 and Hoseinnezhad, R. 2003. Fuzzy clustering approach using data fusion theory and its application to automatic isolated word recognition. International Journal of Engineering (IJE) Transactions B 16 (4) , pp. 329-336.

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Abstract

n this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the proposed algorithms have better performance, compared to classical clustering.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords:	Data Fusion Theory; K-Means Clustering; Fuzzy K-Means; Fuzzy Vector Quantization
ISSN:	1018-7375
Date of Acceptance:	3 November 2003
Last Modified:	21 Oct 2022 07:10
URI:	https://orca.cardiff.ac.uk/id/eprint/99288

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