Date: Wednesday, 29th March 2017 at 2pm
Place: LORIA, room A008
Speaker: Martin Heckmann (Honda Research Institute Europe)
Title: Personalized speech interfaces
Abstract: In this presentation I will highlight recent results obtained at the Honda Research Institute Europe GmbH in the context of personalization of speech-based human-machine interfaces. I will first talk about the detection of word prominence. Thereby, I will discuss the performance of prominence detection from noisy audio signals, the contribution of additional visual information on the speaker’s face and head movements as well as different strategies to fuse the two modalities. After that I will present a method to adapt the prominence detection to an individual speaker. The method is inspired by fMLLR, a well-known method in GMM/HMM-based speech recognition systems, and adapted to the SVM-based prominence detection. Next, I will talk about an advanced driver assistance systems (ADAS) which we currently develop to support the driver in inner-city driving and which is controlled via speech. This system will allow the driver to flexibly formulate his requests for assistance while the situation develops. In particular, when facing a left turn at an intersection the driver can delegate the task of observing the right side traffic to the system as he would do to a co-driver. The system will then inform him when there is an appropriate gap in the traffic to make the turn. Results of a user study we performed show that drivers largely prefer our proposed system to an alternative visual system or driving without any assistance. In this context I will show results on the estimation of the individual driver’s left turning behavior. Based on these driver models the interaction with the driver can be personalized to further improve the usefulness of the system.