ISSN 0021-3454 (print version)
ISSN 2500-0381 (online version)
Menu

9
Issue
vol 60 / SEPTEMBER, 2017
Article
UDC 004.934

ANALYSIS OF DATA BALANCING PROBLEM IN ACOUSTIC MODELING OF AUTOMATIC SPEECH RECOGNITION SYSTEM

N. A. Tomashenko
Laboratory of Computer Science of the University of Le Mans (LIUM), 72085, France; “STC -Innovation” Ltd., 196084, Saint Petersburg ; PhD student; Researcher


Y. Y. Khohlov
STC Ltd., St. Petersburg; Leading Programmer


Read the full article 

Abstract. The problem of data balancing for training of acoustic models for automatic speech recognition system is considered. A metric is proposed which enables an explicit account for the data level in a cluster during triphone clustering. The proposed approach is shown to improve the quality of speech recognition.
Keywords: automatic speech recognition, GMM-HMM, acoustic modeling, acoustic model training, state tying, data balancing, model clustering, triphones