In this contribution it is shown that a good approach for the grapheme-to-phoneme conversion of proper names (e.g. person names, toponyms, etc), is to use a cascade of a general purpose grapheme-to-phoneme (G2P) converter and a special purpose phoneme-to-phoneme (P2P) converter. The G2P produces an initial transcription that is then transformed by the P2P. The latter is automatically trained on reference transcriptions of names belonging to the envisaged name category (e.g. toponyms). The P2P learning process is conceived in such a way that it can take account of high order determinants of pronunciation, such as specific syllables, name prefixes and name suffixes. The proposed methodology was successfully tested on person names and toponyms, but we believe that it will also offer substantial reductions of the cost for building pronunciation lexicons of other name categories.
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