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2016
L. Lu, Kong, L., Dyer, C., Smith, N. A., and Renals, S., “Segmental Recurrent Neural Networks for End-to-end Speech Recognition”, in Proc. INTERSPEECH, 2016.
L. Lu and Renals, S., “Small-footprint Deep Neural Networks with Highway Connections for Speech Recognition”, in Proc. INTERSPEECH, 2016.
2015
P. Bell and Renals, S., “Complementary tasks for context-dependent deep neural network acoustic models”, in Proc. Interspeech, 2015.
L. Lu and Renals, S., “Feature-space Speaker Adaptation for Probabilistic Linear Discriminant Analysis Acoustic Models”, in Proc. INTERSPEECH, 2015.
L. Lu and Renals, S., “Multi-frame factorisation for long-span acoustic modelling”, in Proc. ICASSP, 2015.
A. Ali, Magdy, W., Bell, P., and Renals, S., “Multi-reference WER for evaluating ASR for languages with no orthographic rules”, in Proc. ASRU, 2015.
P. Bell and Renals, S., “Regularization of context-dependent deep neural networks with context-independent multi-task training”, in Proc. ICASSP, 2015.
L. Lu, Zhang, X., Cho, K. H., and Renals, S., “A Study of the Recurrent Neural Network Encoder-Decoder for Large Vocabulary Speech Recognition”, in Proc. INTERSPEECH, 2015.
P. Bell and Renals, S., “A system for automatic alignment of broadcast media captions using weighted finite-state transducers”, in Proc. ASRU, 2015.
2014
P. Bell, Driesen, J., and Renals, S., “Cross-lingual adaptation with multi-task adaptive networks”, in Proc. Interspeech, 2014.
L. Lu, Ghoshal, A., and Renals, S., “Cross-lingual subspace Gaussian mixture model for low-resource speech recognition”, IEEE Transactions on Audio, Speech and Language Processing, 2014.
L. Lu and Renals, S., “Probabilistic Linear Discriminant Analysis for Acoustic Modelling”, IEEE Signal Processing Letters, vol. 21, pp. 702-706, 2014.
L. Lu and Renals, S., “Probabilistic linear discriminant analysis with bottleneck features for speech recognition”, in Proc. INTERSPEECH, 2014.
2013
L. Lu, Ghoshal, A., and Renals, S., “Acoustic Data-driven Pronunciation Lexicon for Large Vocabulary Speech Recognition”, in Proc. IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), 2013.
L. Lu, Chin, K. K., Ghoshal, A., and Renals, S., “Joint Uncertainty Decoding for Noise Robust Subspace Gaussian Mixture Models”, IEEE Transactions on Audio, Speech and Language Processing, 2013.
P. Bell, Yamamoto, H., Swietojanski, P., Wu, Y., McInnes, F., Hori, C., and Renals, S., “A lecture transcription system combining neural network acoustic and language models”, in Proc. Interspeech, Lyon, France, 2013.
P. Bell, Swietojanski, P., and Renals, S., “Multi-level adaptive networks in tandem and hybrid ASR systems”, in Proc. ICASSP, Vancouver, Canada, 2013.
A. Ghoshal, Swietojanski, P., and Renals, S., “Multilingual training of deep neural networks”, in Proc. ICASSP, 2013.
L. Lu, Ghoshal, A., and Renals, S., “Noise adaptive training for subspace Gaussian mixture models”, in INTERSPEECH, 2013.
P. Swietojanski, Ghoshal, A., and Renals, S., “Revisiting Hybrid and GMM-HMM system combination techniques”, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2013.
2012
L. Lu, Ghoshal, A., and Renals, S., “Joint Uncertainty Decoding with Unscented Transform for Noise Robust Subspace Gaussian Mixture Models”, in Proc. SAPA-SCALE Conference, Portland, OR, 2012.
L. Lu, Ghoshal, A., and Renals, S., “Maximum a posteriori adaptation of subspace Gaussian mixture models for cross-lingual speech recognition”, in Proc. IEEE ICASSP, 2012, pp. 4877-4880.
L. Lu, Chin, K. K., Ghoshal, A., and Renals, S., “Noise Compensation for Subspace Gaussian Mixture Models”, in Proc. Interspeech, Portland, OR, 2012.
J. Yamagishi, Veaux, C., King, S., and Renals, S., “Speech synthesis technologies for individuals with vocal disabilities: Voice banking and reconstruction”, Acoustical Science and Technology, vol. 33, pp. 1-5, 2012.
P. Bell, Gales, M., Lanchantin, P., Liu, X., Long, Y., Renals, S., Swietojanski, P., and Woodland, P., “Transcription of multi-genre media archives using out-of-domain data”, in Proc. IEEE Workshop on Spoken Language Technology, Miami, Florida, USA, 2012.

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