  Development of a proper names pronunciation lexicon is usually a manual
effort which can not be avoided. Grapheme to phoneme (G2P) conversion modules,
in literature, are usually rule based and work best for non-proper names in a
particular language. Proper names are foreign to a G2P module. We follow an
optimization approach to enable automatic construction of proper names
pronunciation lexicon. The idea is to construct a small orthogonal set of words
(basis) which can span the set of names in a given database. We propose two
algorithms for the construction of this basis. The transcription lexicon of all
the proper names in a database can be produced by the manual transcription of
only the small set of basis words. We first construct a cost function and show
that the minimization of the cost function results in a basis. We derive
conditions for convergence of this cost function and validate them
experimentally on a very large proper name database. Experiments show the
transcription can be achieved by transcribing a set of small number of basis
words. The algorithms proposed are generic and independent of language; however
performance is better if the proper names have same origin, namely, same
language or geographical region.
