On the bias of the Turing-Good estimate of probabilities

Good´s (1953) estimate, based on Turing´s formula, was suggested for estimating the probabilities of words in text as well as of species in a mixed population and was found particularly useful for the probability of unseen classes. The authors address the issue of bias in Good´s estimate and propose an alternative to reduce this bias. This may be important in the construction of a language model for speech recognition where sparse data and low probability events are key problems