Combining different speech recognizers by using CART classifier

This paper presents out results obtained by experimenting with CART classifier which may be used for creating hybrid speech recognition system. We tried to create speech recognition system which is capable of producing more than 95 % accuracy by recognizing 25 drugs and 25 diseases names. For speech recognizers combination we used CART classifier. By using this classifier we obtained 97.58 % average recognition accuracy. Comparing this experiment results with our earlier results we can see that by using CART classifier we obtained 0.58 % lower results than using 15 Nearest neighbors classifier. In this experiment we tried to combine one native (Lithuanian language) and few foreign speech recognizers: Russian, English and two German recognizers. For the adaptation of foreign language speech recognizers we used text transcribing method which is based on formal rules. Our experiments proved that recognition accuracy improves when few speech recognizers are combined and CART classifier is one of the methods that are suitable for combination task.