19 Nov
1999
Sphinx
Speech Group, CMU-SCS (rkm@cs.cmu.edu)
Beam Search (Pruning)
·Exhaustive
search over large vocabulary too expensive, and unnecessary
·Use a “beam” to
“prune” the set of active HMMs:
·At
start of each frame, find best available path-score S
·Use
a scale-factor f (< 1.0)
to set a pruning threshold T
= S*f
·Deactivate
an HMM if no state in it has path score >= T
·Effect:
No. of active HMMs larger if no clear frontrunner
·Two kinds of
beams:
·To
control active set of HMMs
·No.
of active HMMs per frame typically 10-20% of total space
·To control word exits
taken (and recorded in BP table)
·No.
of words exited typically 10-20 per frame
·Recognition accuracy
essentially unaffected