Joe Frankel - publications

[1] J. Frankel, K. Richmond, S. King, and P. Taylor. An automatic speech recognition system using neural networks and linear dynamic models to recover and model articulatory traces. In Proc. ICLSP, 2000.
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[2] S. King, P. Taylor, J. Frankel, and K. Richmond. Speech recognition via phonetically-featured syllables. In PHONUS, volume 5, pages 15-34, Institute of Phonetics, University of the Saarland, 2000.
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[3] J. Frankel and S. King. Speech recognition in the articulatory domain: investigating an alternative to acoustic HMMs. In Proc. Workshop on Innovations in Speech Processing, 2001.
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[4] J. Frankel and S. King. ASR - articulatory speech recognition. In Proc. Eurospeech, pages 599-602, Aalborg, Denmark, September 2001.
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[5] J. Frankel. Linear dynamic models for automatic speech recognition. PhD thesis, The Centre for Speech Technology Research, Edinburgh University, 2003.
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[6] J. Frankel, M. Wester, and S. King. Articulatory feature recognition using dynamic Bayesian networks. In Proc. ICLSP, 2004.
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[7] M. Wester, J. Frankel, and S. King. Asynchronous articulatory feature recognition using dynamic Bayesian networks. In Proc. IEICI Beyond HMM Workshop, Kyoto, 2004.
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[8] J. Frankel and S. King. A hybrid ANN/DBN approach to articulatory feature recognition. In Proc. Eurospeech, Lisbon, September 2005.
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[9] J. Frankel and S. King. Observation process adaptation for linear dynamic models. Speech Communication, 48(9):1192-1199, September 2006.
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[10] A. Janin, A. Stolcke, X. Anguera, K. Boakye, Ö. Cetin, J. Frankel, and J. Zheng. The ICSI-SRI spring 2006 meeting recognition system. In Proc. MLMI, Washington DC., May 2006.
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[11] J. Frankel and S. King. Speech recognition using linear dynamic models. IEEE Transactions on Speech and Audio Processing, 15(1):246-256, January 2007.
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[12] S. King, J. Frankel, K. Livescu, E. McDermott, K. Richmond, and M. Wester. Speech production knowledge in automatic speech recognition. Journal of the Acoustical Society of America, 121(2):723-742, February 2007.
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[13] K. Livescu, O. Cetin, M. Hasegawa-Johnson, S. King, C. Bartels, N. Borges, A. Kantor, P. Lal, L. Yung, S. Bezman, Dawson-Haggerty, B. Woods, J. Frankel, M. Magimai-Doss, and K. Saenko. Articulatory feature-based methods for acoustic and audio-visual speech recognition: Summary from the 2006 JHU Summer Workshop. In Proc. ICASSP, Honolulu, April 2007.
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[14] O. Cetin, A. Kantor, S. King, C. Bartels, M. Magimai-Doss, J. Frankel, and K. Livescu. An articulatory feature-based tandem approach and factored observation modeling. In Proc. ICASSP, Honolulu, April 2007.
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[15] K. Livescu, A. Bezman, N. Borges, L. Yung, O. Cetin, J. Frankel, S. King, M. Magimai-Doss, X. Chi, and L. Lavoie. Manual transcription of conversational speech at the articulatory feature level. In Proc. ICASSP, Honolulu, April 2007.
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[16] J. Frankel, M. Magimai-Doss, S. King, K. Livescu, and O. Cetin. Articulatory feature classifiers trained on 2000 hours of telephone speech. In Proc. Interspeech, Antwerp, Belgium, August 2007.
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[17] J. Frankel, M Wester, and S. King. Articulatory feature recognition using dynamic Bayesian networks. Computer Speech & Language, 21(4):620-640, October 2007.
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[18] J. Frankel and S. King. Factoring Gaussian precision matrices for linear dynamic models. Pattern Recognition Letters, 27:2264-2272, 2007.
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[19] Ö. Cetin, M. Magimai-Doss, A. Kantor, S. King, C. Bartels, J. Frankel, and K. Livescu. Monolingual and crosslingual comparison of tandem features derived from articulatory and phone MLPs. In Proc. ASRU, Kyoto, December 2007. IEEE.
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