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Publications

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Author Title Type [ Year(Asc)]
2014
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. Eje 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 language models, Computer Speech & Language, vol. 28, pp. 1298–1316, 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.
L. Lu and Renals, S., Probabilistic linear discriminant analysis with bottleneck features for speech recognition, in Proc. INTERSPEECH, 2014.
M. Sinclair, Bell, P., Birch, A., and McInnes, F., A semi-Markov model for speech segmentation with an utterance-break prior, in Proc. Interspeech, 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.
O. Saz and Hain, T., Using Contextual Information in Joint Factor Eigenspace MLLR for Speech Recognition in Diverse Scenarios, in {Proceedings of the 2014 International Conference on Acoustic, Speech and Signal Processing (ICASSP)}, Florence, Italy, 2014, pp. 6314–6318.
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.
2013
, A., G., and S., R., Acoustic Data-driven Pronunciation Lexicon for Large Vocabulary Speech Recognition, in Proc. ASRU, 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.
O. Saz and Hain, T., Asynchronous Factorisation of Speaker and Background with Feature Transforms in Speech Recognition, in {Proceedings of the 14th Annual Conference of the International Speech Communication Association (Interspeech)}, Lyon, France, 2013, pp. 1238–1242.
O. Saz and Hain, T., Asynchronous factorisation of speaker and background with feature transforms in speech recognition, in Proceedings of Interspeech 2013, Lyon, France, 2013.
P. Lanchantin, Bell, P. - J., Gales, M. - J. - F., Hain, T., Liu, X., Long, Y., Quinnell, J., Renals, S., Saz, O., Seigel, M. - S., Swietojanski, P., and Woodland, P. - C., Automatic Transcription of Multi-genre Media Archives, in Proceedings of SLAM Workshop, Marseille, France, 2013.
P. Lanchantin, Bell, P. J., Gales, M. J. F., Hain, T., Liu, X., Long, Y., Quinnell, J., Renals, S., Saz, O., Seigel, M. S., Swietojanski, P., and Woodland, P. C., Automatic Transcription of Multi-Genre Media Archives, in {Proceedings of the First Workshop on Speech, Language and Audio in Multimedia}, Marseille, France, 2013, pp. 26–31.
M. Shannon, Zen, H., and Byrne, W., Autoregressive models for statistical parametric speech synthesis, IEEE Trans. Audio Speech Language Process., vol. 21, pp. 587–597, 2013.
H. Lu, King, S., and Watts, O., Combining a Vector Space Representation of Linguistic Context with a Deep Neural Network for Text-To-Speech Synthesis, in 8th ISCA Workshop on Speech Synthesis, Barcelona, Spain, 2013, pp. 281–285.
H. Christensen, Aniol, M. B., Bell, P., Green, P., Hain, T., King, S., and Swietojanski, P., Combining in-domain and out-of-domain speech data for automatic recognition of disordered speech, in Interspeech'13, 2013.
X. Liu, Gales, M., and Woodland, P., Cross-domain Paraphrasing For Improving Language Modelling Using Out-of-domain Data, in ISCA Interspeech2013, Lyon, France, 2013.

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