Result Details
Cross-Domain and Cross-Language Portability of Acoustic Features Estimated by Multilayer Perceptrons
Grézl František, Ing., Ph.D., DCGM (FIT)
Hwang Mei-Yuh
Lei Xin
Morgan Nelson, prof.
Vergyri Dimitra
Cross domains and language portability of phone-posterior features. English-trained MLP features can provide a significant
boost to recognition accuracy in new domains within the same
language, as well as in entirely different languages such as Mandarin and Arabic.
Cross domains, cross language, portability, probabilistic features, MLP features
Recent results with phone-posterior acoustic features estimated by
multilayer perceptrons (MLPs) have shown that such features can
effectively improve the accuracy of state-of-the-art large vocabulary
speech recognition systems. MLP features are trained discriminatively
to perform phone classification and are therefore,
like acoustic models, tuned to a particular language and application
domain. In this paper we investigate how portable such features
are across domains and languages. We show that even without
retraining, English-trainedMLP features can provide a significant
boost to recognition accuracy in new domainswithin the same
language, as well as in entirely different languages such as Mandarin
and Arabic. We also show the effectiveness of feature-level
adaptation in porting MLP features to new domains.
@inproceedings{BUT22432,
author="Andreas {Stolcke} and František {Grézl} and Mei-Yuh {Hwang} and Xin {Lei} and Nelson {Morgan} and Dimitra {Vergyri}",
title="Cross-Domain and Cross-Language Portability of Acoustic Features Estimated by Multilayer Perceptrons",
booktitle="2006 IEEE International Conference on Acoustic, Speech, and Signal Processing",
year="2006",
pages="321--324",
publisher="IEEE Signal Processing Society",
address="Toulouse",
isbn="978-3-540-74627-0"
}Specifický výzkum, BUT, Vnitřní projekty VUT, SV, start: 2005-01-01, end: 2009-12-31, completed