On Automatic Prominence Detection for German

Perceptual prominence is an important indicator of a word’s and syllable’s lexical, syntactic, semantic and pragmatic status in a discourse. Its automatic annotation would be a valuable enrichment of large databases used in unit selection speech synthesis and speech recognition. While much research has been carried out on the interaction between prominence and acoustic factors, little progress has been made in its automatic annotation. Previous approaches to German relied on linguistic features in prominence detection, but a purely acoustic method would be advantageous. We applied an algorithm to German data that had been previously used for English and Italian. Both the algorithm and the data annotation encode prominence as a continuous rather than a categorical parameter. First results are encouraging, but again show that prominence perception relies on linguistic expectancies as well as acoustic patterns. Also, our results further strengthen the view that force accents are a more reliable cue to prominence than pitch accents in German.