Optimizing Phonetic Encoding for Viennese Unit Selection Speech Synthesis

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.