Influence of features extraction methods in performance of continuous speech recognition for Romanian

被引：0
|
作者：
Dumitru, C. O. [1 ]
Gavat, Inge [1 ]
机构：
[1] Univ Politehn Bucuresti, Fac Elect Telecommun & Informat Technol, Bucharest, Romania
来源：
2007 14TH INTERNATIONAL WORKSHOP ON SYSTEMS, SIGNALS, & IMAGE PROCESSING & EURASIP CONFERENCE FOCUSED ON SPEECH & IMAGE PROCESSING, MULTIMEDIA COMMUNICATIONS & SERVICES | 2007年
关键词：
statistical modelling; HMM; LPC; MFCC; PLP; WRR;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper describes continuous speech recognition experiments for Romanian language, based on statistical modelling by using hidden Markov models. These experiments are made in order to select the most appropriate features extraction method. The compared methods are cepstral and LPC analysis, in standard and perceptual versions. In our tests the cepstral coefficients perform in the most situations better versus the linear prediction ones, and the perceptual coefficients better than the standard ones.
引用
收藏
页码：40 / 43
页数：4
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