Grapheme-to-phoneme conversion (g2p) is a core component of any text-to-speech system. We show that adding simple syllabification and stress assignment constraints, namely ‘one nucleus per syllable’ and ‘one main stress per word’, to a joint n-gram model for g2p conversion leads to a dramatic improvement in conversion accuracy. Secondly, we assessed morphological preprocessing for g2p conversion. While morphological information has been incorporated in some past systems, its contribution has never been quantitatively assessed for German. We compare the relevance of morphological preprocessing with respect to the morphological segmentation method, training set size, the g2p conversion algorithm, and two languages, English and German.
['Vera Demberg', 'Helmut Schmid', 'Gregor M"ohler']
Phonological Constraints and Morphological Preprocessing for Grapheme-to-Phoneme Conversion