Editing Carnegie Mellon's Harpy System (section)

== Key Innovations ==

* Collapsing common sub-networks reduces overall network complexity. This breakthrough allows faster processing by simplifying the network.

* Learning lexical representations and phonemic templates from training data accounts for coarticulation effects. Allophonic variations arespecified in the Harpy system by the use of many unique phones (60) withone template per phone rather than a smal! number of phones with alarge number of templates per phone. Optimizing the dictionary and templates using speech evidence from training data is a breakthrough improving accuracy.

* Calculating state probabilities dynamically makes the system more speech-dependent. This breakthrough improves robustness compared to statistical a priori calculations.

* The HARPY system represents knowledge as a finite state network without a-priori transition probabilities. This breakthrough allows more flexible speech-dependent probability calculations. 

* HARPY only searches a few "best" syntactic and acoustic paths to find the optimal path. This dramatically reduces search complexity compared to examining all possible paths.

* Segmenting the utterance reduces its length effectively, decreasing the number of required state probability updates. This significantly speeds up processing.