Selected publications (out of 60 publications)
Grégoire Mesnil, Yann Dauphin, Kaisheng Yao, Yoshua Bengio, Li Deng, Dilek Hakkani-Tur, Xiaodong He, Larry Heck, Gokhan Tur, Dong Yu, Geoffrey Zweig, "Using recurrent neural networks for slot filling in spoken language understanding", in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 23, no. 3, 2015
K. Yao, B. Peng, G. Zweig, D. Yu, X. Li, and F. Gao, “Recurrent conditional random fields”, in Deep Learning Workshop, NIPS, 2013.
K. Yao, G. Zweig, M. Hwang, Y. Shi and D. Yu, "Recurrent Neural Networks for Language Understanding", in Interspeech, 2013
K. Yao, D. Yu, L. Deng, and Y. Gong, “A fast maximum likelihood nonlinear feature transformation method for GMM-HMM speaker adaptation”, in Neurocomputing, 2013
D. Yu, K. Yao, H. Su, G. Li, and F. Seide, “KL-divergence regularized deep neural network adaptation for improved large vocabulary speech recognition”, in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2013.
D. Povey and K. Yao, “A Basis Representation of Constrained MLLR Transforms for Robust Adaptation”, Computer, Speech, and Language, vol.26, no. 1., 2012.
L. Deng, J.-T. Huang, J. Li, K. Yao, et al, “Recent advances of deep learning for speech research at Microsoft”, in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2013.
K. Yao, D. Yu, F. Seide, H. Su, L. Deng, and Y. Gong, “Adaptation of context-dependent deep neural networks for automatic speech recognition”, in IEEE Spoken Language Technology workshop, 2012.
K. Yao, Y. Gong and C. Liu, “A feature space transformation method for personalization using generalized i-vector clustering”, in INTERSPEECH 2012.
D. Povey and K. Yao, “A basis method for robust estimation of constrained MLLR”, in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2011.
K. K. Paliwal and K. Yao, “Robust Speech Recognition under Noisy Ambient Conditions”, in Human Centric Interface for Ambient Intelligence, edited by R. Delgado, H. Aghajan, and J. Augusto, Elsevier, 2010.
K. Yao, “A noise robust algorithm for underdetermined source separation”, in IEEE Workshop on Statistical Signal Processing, 2009.
K. Yao and L. Netsch, “An approach to low footprint pronunciation models for embedded speaker independent name recognition”, in IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, Hawaii, 2007.
K. Yao, L. Netsch, and V. Viswanathan, “Speaker-independent name recognition using improved compensation and acoustic modeling methods for mobile applications”, in IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 173-176, Toulouse, France, 2006.
K. Yao, K. K. Paliwal, and T.-W. Lee, “Generative factor analyzed HMM for automatic speech recognition”, Speech Communication, vol. 45, no. 4, pp. 435-454, 2005.
K. Yao and T.-W. Lee, “Sequential Monte Carlo Method of Time-Varying Noise Estimation for Speech Enhancement and Recognition”, EURASIP Journal on Applied Signal Processing, vol. 15, pp. 2366-2384, 2004
T.-W. Lee and K. Yao, “Speech enhancement by perceptual filter with sequential noise parameter estimation”, in IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 693-696, Montreal, Canada, 2004.
K. Yao, K. K. Paliwal, and S. Nakamura, “Noise Adaptive Speech Recognition based on Sequential Noise Parameter Estimation”, Speech Communication, vol. 42, no. 1, pp. 5-23, 2004.
H.-Y. Cho, K. Yao, and T.-W. Lee, “Emotion verification for emotion detection and unknown emotion rejection”, in International Conference on Spoken Language Processing, pp. 1345-1348, Jeju Island, Korea, 2004.
K. Yao and T.-W. Lee, “Speech enhancement with noise parameter estimated by a sequential Monte Carlo method”, in IEEE workshop on Statistical Signal Processing, pp. 609-612, St. Louis, U.S.A., 2003.
K. Yao, K. K. Paliwal, T.-W. Lee, “Speech recognition with a generative factor analyzed hidden Markov model”, in EUROSPEECH, 2003.
K. Yao, K. K. Paliwal, S. Nakamura, “Model-based noisy speech recognition with environment parameters estimated by noise adaptive speech recognition with prior”, in EUROSPEECH, 2003.
K. Yao, E. Visser, O.-W. Kwon, and T.-W. Lee, “A speech processing front-end with eigenspace normalization for robust speech recognition in noisy automobile environments”, in EUROSPEECH, pp. 9-12, 2003.
K. Yao, K. K. Paliwal, S. Nakamura, “Noise adaptive speech recognition with acoustic models trained from noisy speech evaluated on Aurora-2 database”, in International Conference on Spoken Language Processing, vol. 4, pp. 2437-2440, Sept., 2002.
K. Yao, K. K. Paliwal, S. Nakamura, “Noise adaptive speech recognition in time-varying noise based on sequential Kullback proximal algorithm”, in IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 1, pp. 189-192, Florida, U.S.A., May, 2002.
K. Yao, J. Chen, K. K. Paliwal, S. Nakamura, “Feature Extraction and Model-based Noise Compensation for Noisy Speech Recognition evaluated on AURORA 2 Task”, in EUROSPEECH, vol.1, pp. 233-236, Denmark, Sept. 2001. Rank 3rd in international competition.
K. Yao, S. Nakamura, “Sequential noise compensation by sequential Monte Carlo method”, in Advances in Neural Information Processing Systems 14, pp. 1205-1212, edited by T. G. Dietterich, S. Becker, and Z. Ghahramani, MIT press, 2001.
K. Yao, S. Nakamura, “Time-varying Noise Compensation by Sequential Monte Carlo Method”, in IEEE Workshop on Automatic Speech Recognition and Understanding, Italy, Dec. 2001.
Y. Xu, J. Zhang, K. Yao, Z. Cao, Y. Wang, “Speech Enhancement Applied to Noisy Speech Recognition”, Journal of Tsinghua University, vol. 41, no. 1, pp. 41-44, 2001.
K. Yao, B. E. Shi, P. Fung, Z. Cao “Log-Add Approximation On-line Noise Compensation using Robust Decision Rules for Robust Digits Recognition”, Chinese Journal of Electronics, vol. 9, no. 3, pp. 278-83, 2000