Title :
Model Adaptation For Spoken Language Understanding
Author_Institution :
AT&T Labs.-Res., USA
fDate :
March 18-23, 2005
Keywords :
error statistics; interactive systems; learning (artificial intelligence); natural languages; signal classification; speech recognition; active learning; classification error rate; intent classification; intent distribution; model adaptation; spoken dialog systems; spoken language understanding; Adaptation model; Boosting; Classification algorithms; Error analysis; Humans; Iterative algorithms; Labeling; Natural languages; Routing; Training data;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
Print_ISBN :
0-7803-8874-7
DOI :
10.1109/ICASSP.2005.1415045