@InProceedings{Siegert2012_140,
<br/>   author = {Ingo Siegert and Ronald Böck and David Philippou-Hübner and Andreas Wendemuth},
<br/>   booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2012.},
<br/>   title = {Investigation of hierarchical classification for simultaneous gender and age recognition},
<br/>   year = {2012},
<br/>   editor = {Matthias Wolff},
<br/>   month = mar,
<br/>   pages = {58--64},
<br/>   publisher = {TUDpress, Dresden},
<br/>   abstract  = {For a successful speech-controled human-machine-interaction individualized
models are needed. If the system is designed to run with many users for short
times each, a complete user adaptation is not useful. A possible solution would be
to use user-group pre-adapted models and recognize the group the actual speaker
belongs to in the very first beginning of the interaction. In this paper we present
investigate different methods to recognize age and gender groups with an hierarchical
model to improve the recognition rate. We could prove, that our method could
get adequate results on a four class problem compared with classical approaches.},
<br/>   isbn = {978-3-942710-81-7},
<br/>   issn = {0940-6832},
<br/>   keywords = {Spracherkennung},
<br/>   url = {https://www.essv.de/pdf/2012_58_64.pdf},
<br/>}