Combining active and semi-supervised learning for spoken...

Data processing: speech signal processing – linguistics – language – Speech signal processing – Recognition

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C704S009000, C704S010000, C704S243000, C704S245000, C704S257000, C706S012000

Reexamination Certificate

active

08010357

ABSTRACT:
Combined active and semi-supervised learning to reduce an amount of manual labeling when training a spoken language understanding model classifier. The classifier may be trained with human-labeled utterance data. Ones of a group of unselected utterance data may be selected for manual labeling via active learning. The classifier may be changed, via semi-supervised learning, based on the selected ones of the unselected utterance data.

REFERENCES:
patent: 6208963 (2001-03-01), Martinez et al.
patent: 6314399 (2001-11-01), Deligne et al.
patent: 7149687 (2006-12-01), Gorin et al.
patent: 7490071 (2009-02-01), Milenova et al.
patent: 7835910 (2010-11-01), Hakkani-Tur et al.
patent: 2003/0083859 (2003-05-01), Murata
patent: 2003/0233369 (2003-12-01), Sassano
patent: 2004/0205482 (2004-10-01), Basu et al.
patent: 2005/0105712 (2005-05-01), Williams et al.
patent: 2005/0182736 (2005-08-01), Castellanos
G. Tur et al. “Active and Semi-Supervised Learning for Spoken Language Understanding” Aug. 7, 2003.
Jin, R., & Si, L. (2004). A bayesian approach toward active learning for collaborative filtering. Proceedings of the 20th conference on Uncertainty in artificial intelligence (pp. 278-285). Banff, Canada: AUAI Press.
S. Tong and D. Koller. Active learning for parameter estimation in Bayesian networks. In NIPS, pp. 647{653, 2000.
S. Tong and D. Koller. Active learning for structure in Bayesian networks. In Proc. IJCAI-01, 2001.
D. Hakkani-Tiir, G. Riccardi, and A. Gorin, “Active learning for automatic speech recognition,” in Proceedings of the ICASSP, 2002.
[Baram et al., 2003] Y. Baram, R. El-Yaniv, and K. Luz. Online choice of active learning algorithms. In Proc. of ICML-2003, pp. 19-26, 2003.
McCallum, A. & Nigam, K. (1998) “Employing EM in Pool-Based Active Learning”, in ICML98.
Tur et al. “Active Labeling for Spoken Language Understanding” 2003.
Schapire et al. “BoosTexter: A Boosting-based System for Text Categorization” 2000.
Schapire et al. “Incorporating Prior Knowledge into Boosting” 2002.
McCallum, Andrew et al “Employing EM in Pool-Based Active Learning for Text Classification”. 15thInternational Conference on Machine Learning (ICML-98). Mar. 1998.
Tür, Gokhan et al. “Active Learning for Spoken Language Understanding”. © 2003 IEEE. AT&T Labs—Research, Florham Park, New Jersey, USA.
Tür, Gokhan et al. “Exploiting Unlabeled Utterances for Spoken Language Understanding”. Eurospeech 2003—Geneva. AT&T Labs—Research, Florham Park, New Jersey, USA.
Musela, Ion et al. “Active + Semi-Supervised Learning = Robust Multi-View Learning”. Information Sciences Institute / University of Southern California, Marina del Rey, California, USA.
Riccardi, Giuseppe et al. “Active and Unsupervised Learning for Automatic Speech Recognition”. AT&T Labs—Research, Florham Park, New Jersey, USA.
Robert E. Shapire, “The boosting approach to machine learning: An overview”, Proceeding of the MSRI Workshop on Nonlinear Estimation and Classification, 2002, pp. 1-23.
G. Tur et al., “Combining active and semi-supervised learning for spoken language understanding”, Speech Communication, Elsevier Science Publishers, Amsterdam, NL, vol. 45, No. 2, Feb. 2005, pp. 171-186.
X. Zhu et al., “Combining active learning and semi-supervised learning using Gaussian Fields and Harmonic Functions”, Proceedings of the ICML 2003, Workshop on the Continuum from Labeled to Unlabeled Data, Aug. 21, 2003.
Musela, Ion et al., “Active + Semi-Supervised Learning = Robust Multi-View Learning”, Information Sciences Institute/University of Southern California, Marina del Rey, California, USA, Jul. 2002.
Riccardi, Giuseppe et al., “Active and Unsupervised Learning for Automatic Speech Recognition”, AT&T Labs—Research, Florham Park, New Jersey, USA, Sep. 2003.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Combining active and semi-supervised learning for spoken... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Combining active and semi-supervised learning for spoken..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Combining active and semi-supervised learning for spoken... will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-2762364

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.