Automatic set-up for speech recognition engines based on merit optimization

We propose an automatic method to set-up the several parameters that define the behavior and performance of a typical speech recognition engine. Such parameters include weights and beam widths among others. Our method is based on the definition of a merit function. Here, merit is understood as an intuitive notion of recognition performance based on both recognition accuracy and computation time. A convenient definition of merit allows an optimization procedure to be applied to define a convenient set-up for the recognizer with little human intervention. The method is applied to adjust the recognition parameters of two different LVCSR (large vocabulary continuous speech recognition) applications, one in American English and another in Japanese.