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The quality of unit selection speech synthesisers depends significantly on the content of the speech database being used. In this paper a technique is introduced that can highlight mispronunciations and abnormal units in the speech synthesis voice database through the use of articulatory acoustic feature extraction to obtain an additional layer of annotation. A set of articulatory acoustic feature classifiers help minimise the selection of inappropriate units in the speech database and are shown to significantly improve the word error rate of a diphone synthesiser.