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.