This version of SCTK contains two programs:
SCTK has at its core, sclite (Score-Lite), which is a flexible Dynamic Programming alignment engine used to "align" errorful hypothesized texts, such as output from an ASR system, to the correct reference texts. After alignment, sclite generates a veriety of summary as well as detailed scoring reports.
This version of sclite comes bundled with the CMU-Cambridge Statistical Language Modeling Toolkit v2. The toolkit is used to compute word-weights based on an N-gram language model. The directory 'src/slm_v2' contains the complete distribution and is automatically compiled by the installation scripts.
While sclite aligns and scores a single system, sc_stats will compare system performance between more than one system, so long as the systems under test have been ran on identical test data and using an identical test paradigm. Inter-System comparisons are made by running tests paired-comparison statistical significance tests.
Rover - Recognition Output Voting Error Reduction, is a tool which combines an arbitrary number for ASR system outputs into a composite Word Transition network which is then searched an scored to retrieve the best scoring word sequence.
The program is documented in the paper A post-processing system to yield reduced word error rates: Recognizer Output Voting Error Reduction (ROVER) presented at the 1997 IEEE Workshop on Automatic Speech Recognition and Understanding. The paper is also available in postscript.