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	title        = {Calculating the reliability of likelihood ratios: Addressing modelling problems related to small n and tails},
	abstract     = {In forensic speech science we are often faced with the problem of having a relatively small amount of data which is also
multivariate and distributionally complex. This results in a serious problem exactly in the scenario where potentially large
strengths of evidence could be obtained, i.e., when the trace data are on a tail of the distribution which models either the
prosecution or defence hypothesis and a large magnitude log likelihood ratio is calculated. By definition the sampling of
a distribution is sparse on its tails and this problem is compounded if the model is trained on a small amount of data – small
fluctuations in the training data can lead to large changes in the calculated likelihoods on the tails and thus large changes
in the calculated likelihood ratios for trace data on the tails. Large-magnitude calculated log likelihood ratios are therefore
inherently unreliable.},
	booktitle    = {Proceedings of 14th Australasian International Conference on Speech Science and Technology},
	author       = {Morrison, Geoffrey Stewart and Ochoa, Felipe and Lindh, Jonas},
	year         = {2012},
	volume       = {14},