  This paper describes an automatic word classification system which uses a
locally optimal annealing algorithm and average class mutual information. A new
word-class representation, the structural tag is introduced and its advantages
for use in statistical language modelling are presented. A summary of some
results with the one million word LOB corpus is given; the algorithm is also
shown to discover the vowel-consonant distinction and displays an ability to
cluster words syntactically in a Latin corpus. Finally, a comparison is made
between the current classification system and several leading alternative
systems, which shows that the current system performs respectably well.
