On Turing's formula for word probabilities
IEEE Transactions on Acoustics Speech and Signal ProcessingPublished 1 December 1985
Arthur Nádas
Citations85
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
It is remarkable that Turing's formula can be obtained by significantly different statistical methods; it is compared three ways to obtain it.
Abstract
A. M. Turing, in a 1941 personal communication to I. J. Good, suggested a formula for estimating probabilities of words in text and, more generally, of species in a mixed population of various species. It is remarkable that Turing's formula can be obtained by significantly different statistical methods; we compare three ways to obtain it.
Keywords
Computer ScienceBiochemistry, Genetics and Molecular Biology
BiometrikaTHE POPULATION FREQUENCIES OF SPECIES AND THE ESTIMATION OF POPULATION PARAMETERS
3,227 Citations1953I. J. Good
Springer series in statisticsAn Empirical Bayes Approach to Statistics
847 Citations1992Herbert Robbins
IEEE Transactions on Acoustics Speech and Signal ProcessingEstimation of probabilities in the language model of the IBM speech recognition system
89 Citations1984Arthur Nádas
The predictive power of the model thus fitted is compared by means of its experimental perplexity to the model as fitted by the Jelinek-Mercer deleted estimator and by the Turing-Good formulas for probabilities of unseen or rarely seen events.
VTechWorks (Virginia Tech)Topics on the estimation of small probabilities.
6 Citations1977Wolfgang Pelz