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Author Title Type [ Year(Asc)]
2014
P. Karanasou, Wang, Y., Gales, M., and Woodland, P., Adaptation of Deep Neural Network Acoustic Models Using Factorised I-vectors, in Proceedings of Interspeech’14, 2014.
I. Casanueva, Christensen, H., Hain, T., and Green, P., "Adaptive speech recognition and dialogue management for users with speech disorders, in Proceedings of Interspeech'14, 2014.
H. Christensen, Casanueva, I., Cunningham, S., Green, P., and Hain, T., Automatic Selection of Speakers for Improved Acoustic Modelling : Recognition of Disordered Speech with Sparse Data, in Spoken Language Technology Workshop, SLT'14, Lake Tahoe, 2014.
P. Swietojanski, Ghoshal, A., and Renals, S., Convolutional Neural Networks for Distant Speech Recognition, Signal Processing Letters, IEEE, vol. 21, pp. 1120-1124, 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.
R. Dall, Wester, M., and Corley, M., The Effect of Filled Pauses and Speaking Rate on Speech Comprehension in Natural, Vocoded and Synthetic Speech, in Proceedings of Interspeech, 2014.
X. Liu, Wang, Y., Chen, X., Gales, M., and Woodland, P., EFFICIENT LATTICE RESCORING USING RECURRENT NEURAL NETWORK LANGUAGE MODELS, in IEEE ICASSP2014, Florence, Italy, 2014.
R. Dall, Tomalin, M., Wester, M., Byrne, W., and King, S., Investigating Automatic & Human Filled Pause Insertion for Speech Synthesis, in Proceedings of Interspeech, 2014.
T. Merritt, Raitio, T., and King, S., Investigating source and filter contributions, and their interaction, to statistical parametric speech synthesis, in Proc. Interspeech, Singapore, 2014, pp. 1509–1513.
P. Swietojanski and Renals, S., Learning Hidden Unit Contributions for Unsupervised Speaker Adaptation of Neural Network Acoustic Models, in Proc. IEEE Workshop on Spoken Language Technology, Lake Tahoe, USA, 2014.
G. E. Henter, Merritt, T., Shannon, M., Mayo, C., and King, S., Measuring the perceptual effects of modelling assumptions in speech synthesis using stimuli constructed from repeated natural speech, in Proceedings of Interspeech, Singapore, 2014.
P. Lanchantin, Gales, M. J. F., King, S., and Yamagishi, J., Multiple-Average-Voice-based Speech Synthesis, in Proc. ICASSP, 2014.
S. Renals and Swietojanski, P., Neural Networks for Distant Speech Recognition, in The 4th Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA), 2014.
X. Liu, Gales, M., and Woodland, P., PARAPHRASTIC NEURAL NETWORK LANGUAGE MODELS, in IEEE ICASSP2014, Florence, Italy, 2014.
L. Lu and Renals, S., Probabilistic Linear Discriminant Analysis for Acoustic Modelling, IEEE Signal Processing Letters, vol. 21, pp. 702-706, 2014.
P. Zhang, Liu, Y., and Hain, T., Semi-Supervised DNN Training in Meeting Recognition, presented at the December, South Lake Tahoe, USA, 2014.
C. Zhang and Woodland, P. C., Standalone training of context-dependent deep neural network acoustic models, in IEEE ICASSP 2014, Florence, Italy, 2014.
O. Saz and Hain, T., Using Contextual Information in Joint Factor Eigenspace MLLR for Speech Recognition in Diverse Scenarios, in Proceedings of the 2014 ICASSP, Florence, Italy., 2014.
C. Valentini-Botinhao and Wester, M., Using linguistic predictability and the Lombard effect to increase the intelligibility of synthetic speech in noise, in Proceedings of Interspeech, 2014.
Y. Liu, Zhang, P., and Hain, T., Using neural network front-ends on far field multiple microphones based speech recognition, in ICASSP2014 - Speech and Language Processing (ICASSP2014 - SLTC), Florence, Italy, 2014.

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