@inproceedings{LongtonJackson_UKSpeech08,
        AUTHOR  =       "Longton, J. and Jackson, P. J. B.",
        TITLE   =       "Parallel model combination and digit recognition with soccer audio",
        BOOKTITLE =	"Proc.\ One-day Mtg. for Young Spch.\ Res. (UK Speech'08)",
	ADDRESS =	"Guildford, UK",
        PAGES   =       "30",
        MONTH   =       "July",
        YEAR    =       "2008",
	ABSTRACT = 
"Audio from broadcast soccer can be used for identifying highlights from 
the game. We can assume that the basic construction of the auditory scene 
consists of two additive parallel audio streams, one relating to 
commentator speech and the other relating to audio captured from the ground 
level microphones. Audio cues derived from these sources provide valuable 
information about game events, as can the detection of key words used by 
the commentators, which are useful for identifying highlights. We 
investigate word recognition in a connected digit experiment providing 
additive noise that is present in broadcast soccer audio. A limited set of 
background soccer noises, extracted from the FIFA World Cup 2006 
recordings, were used to create an extension to the Aurora-2 database. The 
extended data set was tested with various HMM and parallel model 
combination (PMC) configurations, and compared to the standard baseline, 
with clean and multi-condition training methods. It was found that 
incorporating SNR and noise type information into the PMC process was 
beneficial to recognition performance with a reduction in word error rate 
from 17.5% to 16.3% over the next best scheme when using the SNR 
information.Future work will look at non stationary soccer noise types and 
multiple statenoise models."
}