Asian Journal of Information Technology

Year: 2013
Volume: 12
Issue: 1
Page No. 7 - 13

Analysis of Various Efforts to Compensate for Automatic Speech Recognition Deficiencies in Spoken Dialogue System

Authors : S. Lokesh and G. Balakrishnan

References

Bellegarda, J.R., 1998. Multi-Span statistical language modeling for large vocabulary speech recognition. Proceedings of the International Conference on Spoken Language Processing, December 4, 1998, Sydney, Australia, pp: 2395-2399.

Brill, E., R. Florian, J.C. Henderson and L. Mangu, 1998. Beyond N-grams: Can linguistic sophistication improve language modeling? Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics-Volume 1, August 10-14, 1998, Morgan Kaufmann Publishers, San Francisco, CA., pp: 186-190.

Doddington, G., W. Liggett, A. Martin, M. Przybocki and D. Reynolds, 1998. Sheep, goats, lambs and wolves: A statistical analysis of speaker performance in the NIST 1998 speaker recognition evaluation. Proceedings of the 5th International Conference on Spoken Language Processing, November 30-December 4, 1998, Sydney, Australia -.

Genevieve, G., 2006. Generalized hebbian algorithm for incremental singular value decomposition in natural language processing. Proceedings of the 11st Conference of the European Chapter of the Association for Computational Linguistics, April 3-7, 2006, Trento, Italy, pp: 97-104.

Glass, J., 1999. Challenges for spoken dialogue systems. Proceedings of IEEE ASRU Workshop, December 1999, Keystone, CO., pp. 307-310.

Godfrey, J.J. and E. Holliman, 1997. Switchboard-1 release 2. Linguistic Data Consortium, Philadelphia.

Gorrell, G. and B. Webb, 2005. Generalized hebbian algorithm for latent semantic analysis. Proceedings of the 9th European Conference on Speech Communication and Technology, September 4-8, 2005, Lisbon, Portugal, pp: 1325-1328.

Gorrell, G., 2007. Generalized hebbian algorithm for dimensionality reduction in natural language processing. Ph.D. Thesis, Linkoping University, Sweden.

Hermansky, H., 1998. Should recognizers have ears? Speech Commun., 25: 3-27.
CrossRef  |  

Hung, X., A. Acero and H.W. Hon, 2001. Spoken Language Processing, a Guide to Theory, Algorithm and System Development. 1st Edn., Prentice Hall Inc., USA., ISBN-10: 0130226165, pp: 980.

Jelinek, F., 1991. The struggle for improved language models. Proceedings of Eurospeech, September 24-26, 1991, Genova, Italy, pp: 1037-1040.

Jurafsky, D. and J.H. Martin, 2008. Speech and Language Processing. Prentice Hall, New Jersey.

Lindblom, B., 1990. Explaining Phonetic Variation: A Sketch of the H and H Theory. In: Speech Production and Speech Modeling, Hardcastle, W.J. and A. Marchal (Eds.). Kluwer Academic Publisher, The Netherlands, pp: 403-439.

Lippmann, R.P., 1997. Speech recognition by machines and humans. Speech Commun., 22: 1-15.
CrossRef  |  

Manny, R., D. Carter, V. Digalakis and P. Price, 1994. Combining knowledge sources to reorder N-best speech hypothesis lists. Proceedings of the Human Language Technology Workshop, September 1, 1994, Plainsboro, NJ., pp: 219-221.

Moore, R.C., 1999. Using natural-language knowledge sources in speech recognition, in computational models of speech pattern processing. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.27.2954.

Moore, R.K., 2005. Spoken language processing: Piecing together puzzle. Speech Commun., 49: 418-435.
CrossRef  |  

Quesada, J.F., J.G. Amores, P. Manchon, K. Perez, S. Milward and D. Thomas, 2002. Possibilities for enhancing speech recognition by Consulting Information States. Deliverable D2.3, SIRIDUS, http://citeseer.uark.edu:8080/citeseerx/showciting;jsessionid=4038B13447D6A5C09C0CCD2ED1FA9B90?cid=684160.

Raux, A., B. Langner, D. Bohus, A.W. Black and M. Eskenazi, 2005. Let's go public! Taking a spoken dialog system to the real world. Proceedings of the Interspeech'2005-Eurospeech, 9th European Conference on Speech Communication and Technology, September 4-8, 2005, Lisbon, Portugal, pp: 885-888.

Solsona, R.A., E.F. Lussier, H.K.J. Kuo, A. Potamianos and I. Zitouni, 2002. Adaptive language models for spoken dialogue systems. Proceedings of the International Conference on Acoustic Speech and Signal Processing, Vol. 1, April 2007, Orlando, Florida, pp: 37-40.

Soltau, H. and A. Waibel, 2000. Specialized acoustic models for hyperarticulated speech. Proceedings of the International Conference on Acoustics, Speech and Signal Processing, (ASSP'00), Istanbul, Turkey, pp: 1779-1782.

Steve, G. and J.T. Chien, 2012. Large-vocabulary continuous speech recognition systems: A look at some recent advances. IEEE Signal Proces. Magazine, 6: 18-33.
CrossRef  |  

Stolcke, A., 2002. SRILM: An extensible language modeling toolkit. Proceedings of the International Conference on Spoken Language Processing, September 2002, Denver, CO., pp: 901-904.

Weintraub, M., K. Taussig, K. Hunicke-Smith and A. Snodgrass, 1996. Effect of speaking style on LVCSR performance. Proceedings of International Conference on Spoken Language Processing, October 3-6, 1996, Philadelphia, PA., pp: 16-19.

Wilson, S.M., A.P. Saygin, M.I. Sereno and M. Iacoboni, 2004. Listening to speech activates motor areas involved in speech production. Nat. NeuroSci., 7: 701-702.
PubMed  |  Direct Link  |  

Xu, W. and A. Rudnicky, 2000. Can artificial neural networks learn language models. Proceedings of the International Conference on Spoken Language Processing Vol. 1, October 13-15, 2000, Beijing, China, pp: 202-205.

Zhang, R. and A.I. Rudnicky, 2002. Improve latent semantic analysis based language model by integrating multiple level knowledge. Proceedings of the International Conference on Spoken Language Processing, September 2002, Denver, CO., pp: 893-896.

Design and power by Medwell Web Development Team. © Medwell Publishing 2024 All Rights Reserved