Use of center of gravity with the common vector approach in isolated word recognition

GÜLMEZOĞLU M. B., EDİZKAN R., ERGİN S., BARKANA A.

EXPERT SYSTEMS WITH APPLICATIONS, vol.38, no.4, pp.3690-3696, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 38 Issue: 4
  • Publication Date: 2011
  • Doi Number: 10.1016/j.eswa.2010.09.026
  • Journal Name: EXPERT SYSTEMS WITH APPLICATIONS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.3690-3696
  • Keywords: Center of gravity, Endpoint detection, Common vector approach, Speech recognition, END-POINT DETECTION, SPEECH
  • Anadolu University Affiliated: Yes

Abstract

In this paper, the subspace based classifier, common vector approach (CVA), with the center of gravity (COG) method is used for isolated word recognition. Since the CVA classifier is sensitive to shifts through the time axis, endpoint detection becomes extremely important for the recognition of isolated words. The COG method eliminates the need for endpoint detection. The effects of the COG method and a classical endpoint detection algorithm on the recognition rates of isolated words are investigated. The experimental results show that the COG method yields slightly higher recognition rates than the endpoint detection method in the TI-digit database when CVA is used. (C) 2010 Elsevier Ltd. All rights reserved.