Editing Carnegie Mellon's Harpy System (section)

=== '''5. Increasing speed and accuracy''' ===

==== '''5.1 Prior state information saving''' ====
The Harpy system optimized the prior state information saving strategy in Dragon system to reach higher recognition speed. Harpy saves a small number of prior states (100 times samples worth) in memory at a time and when more room is needed, they are saved on external storage (a high speed drum). For the algorithms, Harpy calculates the probabilities by logs and thus do addition, which eliminates the need to scale.

==== '''5.2 Search space reduction''' ====
The Harpy system uses heuristics to reduce the calculations and search spaces, and therefore increases the speed of recognition. The formula for the reaction time shown as below:

'''''(rec.time in seconds)= (#time samples)(.022+.0004(#templates)+.00027(#states)+.00005(# pointers)'''''

The formula shows the 4 main areas where Harpy applies heuristics: '''the number of time samples used''', the number of '''templates''' used for the acoustic match probabilities per time sample, the number of '''states''' checked per time sample, and the number of '''pointers''' checked per time sample.  

The methods used by Harpy to reduce all these number checked per time are based on the notion that '''not all network state probabilities need be updated every time sample'''. At time sample 0, there is probability 1 of being in the initial state and probability of being in all other states. The only states that have non-zero probability at time sample 1 are those states that can be reached in one transition from the initial state. Similarly, the only states that have non-zero probability at time ample N are those states that can be reached in N transitions (both inter and intra-state) from the initial state. At M time samples from the end of the utterance, the only states that need be checked are those from which the final state can be reached in M transitions. Unfortunately, this significantly reduces the number of states that need to be checked only near the start or end of the utterance. Intuitively, the only paths that need to be checked at every time sample are those that are "obvious".

The number of pointers checked at every time sample is dependent on the number of states checked.

The Harpy system uses ‘best-several’ search strategy to reduce the number of paths checked and guarantee the performance in large search space conditions. That is, Harpy searches for a few ‘best’ paths in parallel. ‘best’ is calculated by heuristics.

==== 5.3 State Size reduction ====
The recognition time is dependent upon the confusability among the paths in the Harpy system. The developers removed '''null states, redundant states''', and subsumed '''common states''' to reduce the network size and complexity. The former two removals have no effect on speech recognition accuracy, while the last removal has the potential influencing the recognition process.

* A null state is a state contains no synthetic or phonetic information other than the connections to its prior and following states. Harpy removes null states by linking each of it prior states to each of its following states and deleting the null states. However, the removal of null states increases the number of pointers.
* Two redundant states are 1) same terminal lexical symbol and same prior states or 2) same terminal lexical symbol and same following states. One of the states is selected and removed by Harpy.
* Two states are common if they both have the same phone and 1) same prior states or 2) same following states. Similarly, one state is selected and removed. To avoid danger of completely losing grammatical information due to subsumption of homonyms, the special character ‘!’ may use in the acoustic dictionary to indicate the network compiler.