Studies on Feature Extraction and Discrimination of Spoken Languages.

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This study has attempted to develop a method of spoken language classification based on fundamental frequency (Fo) contours of speech. Speech data ware taken from a CD-ROM Multi-language Speech Database. The speech data of 6 languages were chosen from Asian and European languages. First, Fo contour was approximated by a set of polygonal lines so that the mean square error between the lines and Fo values was minimized ; the optimum boudaries of the lines were determined using a dynamic programming procedure. The starting frequency, slope and duration of each line were calculated. Secondly, parameters derived from Fo pattern were analyzed by using principal component analysis and discriminant analyis. Parameters including mean values and standard deviations of the above parameters were used for the analysis. Results show that the 6 languages can be classified based on these parameters.