Erratum to: A Statistical Approach to 
Machine Translation 
Peter E Brown 
Stephen A. Della Pietra 
Fredrick Jelinek 
Robert L. Mercer 
John Cocke 
Vincent J. Della Pietra 
John D. Lafferty 
Paul S. Roossin 
In Section 6 of "A statistical approach to machine translation" (Computational Linguis- 
tics 16(2), 79-85), we reported the results of two experiments in which we estimated 
parameters of a statistical model of translation from English to French. 
In the first experiment, the English and French vocabularies each consisted of 
9,000 common words, and the model parameters were estimated from 40,000 pairs of 
sentences 25 words or less in length. Words outside the 9,000-word vocabularies in 
these sentences were mapped to special unknown words. 
In the second experiment, the vocabularies were limited to 1,000 common English 
words and 1,700 common French words, and the model parameters were estimated 
from 117,000 pairs of sentences 10 words or less in length that were completely covered 
by the respective vocabularies. 
In Figures 4, 5, and 6 of the paper, we erroneously presented parameter estimates 
from the 1,000-word experiment, while claiming in the text that they were from the 
9,000-word experiment. The parameter estimates for these two experiments differ con- 
siderably because of the restriction of the training corpus in the 1,000-word experiment 
to short, covered sentences. For example, the probability that hear is translated as bravo 
English: the 
French Probability 
le .443 
la .207 
les .184 
\]' .097 
ce .018 
il .012 
Fertility Probability 
1 .856 
0 .140 
Figure 4 
Probabilites for the. 
(~) 1991 Association for Computational Linguistics 
Computational Linguistics Volume 17, Number 3 
English: not 
French Probability Fertility 
ne .482 2 
pas .455 0 
non .029 1 
rein .012 
Probability 
.728 
.153 
.114 
Figure 5 
Probabilities for not. 
English: hear 
French Probability 
bravo .808 
entendre .079 
entendu .026 
entends .024 
entendons .013 
Fertility Probability 
1 .527 
0 .472 
Figure 6 
Probabilities for hear. 
is .992 in the 1,000-word experiment (see Figure 6 of the paper) 1, while it is only .808 
in the 9,000-word experiment (see Figure 6 above). This difference is due to the fact 
that the sentence pair (Hear, hear! \[ Bravo!) is extremely common in our data and is 
completely covered by the 1,000-word and 1,700-word vocabularies. 
Figures 4, 5, and 6 contain the parameter estimates from the 9,000-word experi- 
ment. Only probabilities greater than or equal to .01 are reported. 
1 We thank Ken Church for pointing out that this estimate is not consistent with the frequency with 
which hear translates to bravo in other data from the same source. 
326 
