Optimizing phonetic encoding for viennese unit selection speech synthesis

  • Authors:

  • Michael Pucher;Friedrich Neubarth;Volker Strom

  • Affiliations:

  • Telecommunications Research Center Vienna (ftw.), Vienna, Austria;Austrian Research Institute for Artificial Intelligence (OFAI), Vienna, Austria;Centre for Speech Technology Research (CSTR), University of Edinburgh, UK

  • Venue:
  • COST'09 Proceedings of the Second international conference on Development of Multimodal Interfaces: active Listening and Synchrony
  • Year:
  • 2009

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Abstract

While developing lexical resources for a particular language variety (Viennese), we experimented with a set of 5 different phonetic encodings, termed phone sets, used for unit selection speech synthesis. We started with a very rich phone set based on phonological considerations and covering as much phonetic variability as possible, which was then reduced to smaller sets by applying transformation rules that map or merge phone symbols. The optimal trade-off was found measuring the phone error rates of automatically learnt grapheme-to-phone rules and by a perceptual evaluation of 27 representative synthesized sentences. Further, we describe a method to semi-automatically enlarge the lexical resources for the target language variety using a lexicon base for Standard Austrian German.