In this paper we discuss various experimental results using our continuous speech recognition system on the Wall Street Jounal task. Experiments with different feature extraction methods, varying amounts and type of training data, and different vocabulary sizes are reported. 1 INTRODUCTION Large vocabulary continuous speech recognition is an area that is of great current interest, and to this end, several speech recognition systems have evolved that are capable of dealing with such recognition tasks [2, 4, 5, 6, 7, 9]. The ARPA sponsored Wall Street Journal task represents a standardized database that enables the evaluation of the features specific to these different systems on a common platform. In this paper, we present the performance of the IBM continuous speech recognition system on this task. We will concentrate on the speaker-independent portion of the database. The test data used in the experiments is read speech recorded using a Sennheiser microphone. We report experimental ...