Analysis on individual differences in automatic transcription of spontaneous presentations

This paper reports an analysis of individual differences in spontaneous presentation speech recognition performances. Ten minutes from each presentation given by 50 male speakers, for a total of 500 minutes, has been automatically recognized for the analysis. Correlation and regression analyses were applied to the word recognition accuracy and various speaker attributes. A restricted set of the speaker attributes comprising the speaking rate, the out of vocabulary rate and the repair rate was found to be most significant to yield individual differences in the word accuracy. Unsupervised MLLR speaker adaptation worked well for improving the word accuracy but did not change the structure of the individual differences. Approximately half of the variance in the word accuracy was explained by a regression model using the limited set of three attributes.