Thus, a constant data rate was not guaranteed. Of the 500 sentences collected, six were eliminated due to subject error or outlier signs. In general, each sign was 1 to 3 seconds long. For recognition, HTK's Viterbi recognizer is used both with and without a strong grammar based on the known form of the sentences. Contexts are not used, since a similar effect could be achieved with the strong grammar given this data set.
Recognition occurs five times faster than real time.
When testing on training, all 494 sentences were used for both the test and train sets. For the fair test, the sentences were divided into a set of 395 training sentences and a set of 99 independent test sentences. The 99 test sentences were not used for any portion of the training. However, without the grammar, the recognizer is allowed to match the observation vectors with any number of the 40 vocabulary words in any order. The absolute number of errors of each type are listed in Table 2 .