Whereas speech scientists have focused on carefully pronounced speech for a long time, the interest has more and more shifted to language as it occurs in natural conversations. This has two reasons. From a technological point of view, there is an increasing demand for social robots, which in order to become more interactional and social also need to use language naturally. Second, linguists became more interested in natural conversations, as they reveal additional insights to controlled experiments with respect to how speech is processed in our brain. In this project, we aim at improving the automatic recognition of conversational speech, at increasing our knowledge about the human production and perception of conversational speech, and to increase our knowledge and resources for conversational Austrian German.
On the basis of conversational speech and chat corpora from German and Austrian speakers, we develop “cross-layered” language models which include acoustic and semantic contextual information the way humans do. These models will be informed by quantitative phonetic corpus studies and tested in ASR and speech perception experiments. For conducting the linguistic studies, speech technology will be used for creating automatic annotations, acoustic feature extraction and data analysis. Gained linguistic knowledge will then again be incorporated into the language models. This approach requires an interdisciplinary team (engineers and linguists) that works closely together.