Improvement of a speech recognizer for standardized medical assessment of children's speech by integration of prior knowledge

Tobias Bocklet, Andreas Maier, Ulrich Eysholdt, Elmar Noth
2010 2010 IEEE Spoken Language Technology Workshop  
Speech recognition of children is a more difficult task than speech recognition of adults. This problem is amplified for children with articulation disorders like cleft lip and palate (CLP). In this work we improved our automatic speech recognition system by integrating prior knowledge. Prior knowledge focuses on two different aspects: A testdependent language modeling and an age-dependent acoustic modeling. These two approaches are merged at the end to different test-and age-dependent
more » ... -dependent recognizers. We evaluated our system on a dataset of 35 children with CLP. Significant improvements could be found on this dataset. With our baseline system we achieved a negative word accuarcy (WA) of -11.0 %. By an extended language modeling we achieved 27.5 %. The age-dependent recognition system gains a huge improvement and achieves a WA of 42.6 %. With the significant improvements in WA it is possible to perform an automatic detection and identification of specific words. Thus, we took the first step towards a speech assessment on word and subword level.
doi:10.1109/slt.2010.5700861 dblp:conf/slt/BockletMEN10 fatcat:m5nk6mmiyrdrpfuea4rn5ikycu