Syntactic{prosodic Labeling of Large Spontaneous Speech Data{bases Syntactic{prosodic Labeling of Large Spontaneous Speech Data{bases

Das diesem Bericht zugrundeliegende Forschungsvorhaben wurde mit Mitteln des Bundesministers f ur Bildung, Wissenschaft, Forschung und Technologie unter dem F orderkennzeichen 01 IV 102 F/4 und 01 IV 102 H/0 gef ordert. Die Verantwortung f ur den Inhalt dieser Arbeit liegt bei den Autoren. ABSTRACT In automatic speech understanding, the division of continuously running speech into syntactic chunks is a great problem. Syntactic boundaries are often marked by prosodic means. For the training of statistic models for prosodic boundaries large databases are necessary. For the German Verb-mobil project (automatic speech{to{speech translation), we developed a syntactic-prosodic labeling scheme where two main types of boundaries (major syntactic boundaries and syntactically ambiguous boundaries) and some other special boundaries are labeled for a large Verbmobil spontaneous speech corpus. We compare the results of classiiers (multi-layer perceptrons and language models) trained on these syntactic{prosodic boundary labels with classiiers trained on perceptual{prosodic and pure syntactic labels. The main advantage of the rough syntactic{prosodic labels presented in this paper is that large amounts of data could be labeled within a short time. Therefore, the classiiers trained with these labels turned out to be superior (recognition rates of up to 96%).