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An active learning approach for statistical spoken language understanding

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An active learning approach for statistical spoken language understanding

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García Granada, F.; Hurtado Oliver, LF.; Sanchís Arnal, E.; Segarra Soriano, E. (2011). An active learning approach for statistical spoken language understanding. En Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Verlag (Germany). 7042:565-572. doi:10.1007/978-3-642-25085-9_67

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/38643

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Title: An active learning approach for statistical spoken language understanding
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
In general, large amount of segmented and labeled data is needed to estimate statistical language understanding systems. In recent years, different approaches have been proposed to reduce the segmentation and labeling ...[+]
Subjects: Active learning , Unaligned corpus , Spoken language understanding , Spoken dialog systems
Copyrigths: Reserva de todos los derechos
ISBN: 978-3-642-25084-2
Source:
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. (issn: 0302-9743 )
DOI: 10.1007/978-3-642-25085-9_67
Publisher:
Springer Verlag (Germany)
Publisher version: http://link.springer.com/chapter/10.1007%2F978-3-642-25085-9_67
Conference name: 16th Iberoamerican Congress, CIARP
Conference place: Pucón, Chile
Conference date: November 15-18, 2011
Series: Lecture Notes in Computer Science;
Description: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-25085-9_67
Type: Capítulo de libro

References

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Fraser, M., Gilbert, G.: Simulating speech systems. Computer Speech and Language 5, 81–99 (1991)

Gotab, P., Bechet, F., Damnati, G.: Active learning for rule-based and corpus-based spoken labguage understanding moldes. In: IEEE Workshop Automatic Speech Recognition and Understanding (ASRU 2009), pp. 444–449 (2009) [+]
De Mori, R., Bechet, F., Hakkani-Tur, D., McTear, M., Riccardi, G., Tur, G.: Spoken language understanding: A survey. IEEE Signal Processing Magazine 25(3), 50–58 (2008)

Fraser, M., Gilbert, G.: Simulating speech systems. Computer Speech and Language 5, 81–99 (1991)

Gotab, P., Bechet, F., Damnati, G.: Active learning for rule-based and corpus-based spoken labguage understanding moldes. In: IEEE Workshop Automatic Speech Recognition and Understanding (ASRU 2009), pp. 444–449 (2009)

Gotab, P., Damnati, G., Becher, F., Delphin-Poulat, L.: Online slu model adaptation with a partial oracle. In: Proc. of InterSpeech 2010, Makuhari, Chiba, Japan, pp. 2862–2865 (2010)

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Ortega, L., Galiano, I., Hurtado, L.F., Sanchis, E., Segarra, E.: A statistical segment-based approach for spoken language understanding. In: Proc. of InterSpeech 2010, Makuhari, Chiba, Japan, pp. 1836–1839 (2010)

Riccardi, G., Hakkani-Tur, D.: Active learning: theory and applications to automatic speech recognition. IEEE Transactions on Speech and Audio Processing 13(4), 504–511 (2005)

Segarra, E., Sanchis, E., Galiano, M., García, F., Hurtado, L.: Extracting Semantic Information Through Automatic Learning Techniques. International Journal of Pattern Recognition and Artificial Intelligence 16(3), 301–307 (2002)

Tur, G., Hakkani-Tr, D., Schapire, R.E.: Combining active and semi-supervised learning for spoken language understanding. Speech Communication 45, 171–186 (2005)

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