logo Idiap Research Institute        
 [BibTeX] [Marc21]
Boosting HMMs with an application to speech recognition
Type of publication: Conference paper
Citation: icassp:DimitrakBengio2004
Booktitle: IEEE International Conference on Acoustic, Speech, and Signal Processing, ICASSP
Year: 2004
Note: IDIAP-RR 03-41
Crossref: dimitrakbengio2003a:
Abstract: Boosting is a general method for training an ensemble of classifiers with a view to improving performance relative to that of a single classifier. While the original AdaBoost algorithm has been defined for classification tasks, the current work examines its applicability to sequence learning problems. In particular, different methods for training HMMs on sequences and for combining their output are investigated in the context of automatic speech recognition.
Userfields: ipdmembership={learning},
Projects Idiap
Authors Dimitrakakis, Christos
Bengio, Samy
Added by: [UNK]
Total mark: 0
  • dimitrak_bengio03b.pdf
  • dimitrak_bengio03b.ps.gz