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Revision with unchanged content. Grapheme-to-phoneme conversion (g2p) is a core component of any text-to-speech system. This book discusses how 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. The model is evaluated on German, English and French, and compares well to state-of-the-art approaches. Secondly, the benefit to be gained from morphological preprocessing for g2p conversion is assessed. 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. This work is particularly valuabel for professionals working with speech syntesis systems.

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Dipl.-Ling., MSc: Studied Computational Lingistics at the Institut für Maschinelle Sprachverarbeitung (IMS), University of Stuttgart and Artificial Intelligence at The University of Edinburgh. She is now a PhD student at the School of Informatics, The University of Edinburgh.

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