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BURGET, L., DUPONT, S., GARUDADRI, H., GRÉZL, F., HEŘMANSKÝ, H., JAIN, P., KAJAREKAR, S., MORGAN, N.
Originální název
QUALCOMM-ICSI-OGI Features for ASR
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Our feature extraction module for the Aurora task is based on a combination of a conventional noise supression technique (Wiener filtering) with our temporal processing technigues (linear discriminant RASTA filtering and nonlinear TempoRAl Pattern (TRAP) classifier). We observe better than 58% relative error improvement on the prescribed Aurora Digit Task, a performance level that is somewhat better than the new ETSI Advanced Feature standard. Furthermore, to test generalization of our approach to an independent test set not available during development, we evaluate performance on American English SpeechDatCar digits and show 10.54% relative improvement over the new ETSI standard.
Klíčová slova
feature extraction, distributed speech recognition, Aurora task, RASTA, TRAP
Autoři
Rok RIV
2002
Vydáno
20. 9. 2002
Nakladatel
International Speech Communication Association
Místo
Denver
ISBN
1-876346-42-6
Kniha
Proc. 7th International Conference on Spoken Language Processing
Strany od
4
Strany do
7
Strany počet
URL
http://www.fit.vutbr.cz/~burget/phd_activities/adami_icslp02.pdf
BibTex
@inproceedings{BUT10471, author="Lukáš {Burget} and Stephane {Dupont} and Harinath {Garudadri} and František {Grézl} and Hynek {Heřmanský} and Pratibha {Jain} and Sachin {Kajarekar} and Nelson {Morgan}", title="QUALCOMM-ICSI-OGI Features for ASR", booktitle="Proc. 7th International Conference on Spoken Language Processing", year="2002", pages="4", publisher="International Speech Communication Association", address="Denver", isbn="1-876346-42-6", url="http://www.fit.vutbr.cz/~burget/phd_activities/adami_icslp02.pdf" }