EUROSPEECH 2003 - INTERSPEECH 2003
In this paper we show how to exploit raw speech data to gain higher level information about the user in a mobile context. In particular we introduce an approach for the estimation of age and gender using well known machine learning techniques. On the basis of this information, systems like for example a mobile pedestrian navigation system, can be made adaptive to the special needs of a specific user group (here the elderly). First we provide a motivation why we consider such an adaptation as necessary, then we outline some adaptation strategies that are adequate for mobile assistants. The major part of the paper is about (a) identifying and extracting features of speech that are relevant for age and gender estimation and (b) classifying a particular speaker, treating uncertainty, and updating the user model over time. Finally we provide a short outlook on current work.
Bibliographic reference. Muller, Christian / Wittig, Frank / Baus, Jorg (2003): "Exploiting speech for recognizing elderly users to respond to their special needs", In EUROSPEECH-2003, 1305-1308.