Hill-Climbing Ensemble Feature Selection with a Larger Ensemble

TitleHill-Climbing Ensemble Feature Selection with a Larger Ensemble
Publication TypeTechnical Report
Year of Publication2009
AuthorsGelbart, D.
Other Numbers2706

This report follows up on the investigation of hill-climbing ensemble feature selection for multi-stream speech recognition in David Gelbart's Ph.D. thesis. We compare using three streams as in the thesis to using five streams, to investigate the hypothesis that hill-climbing would give larger accuracy gains with more streams due to there being more feature selection options available. To move from three streams to five streams we split the MFCC and PLP streams into separate streams of static and dynamic features. We find that hill-climbing with five streams does result in better word recognition accuracy than three streams. This may be because our hypothesis is correct, but it also might be because the initial five stream systems that hill-climbing started from were more accurate than the initial three stream systems.

Bibliographic Notes

ICSI Technical Report TR-09-001

Abbreviated Authors

D. Gelbart

ICSI Research Group


ICSI Publication Type

Technical Report