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Publications

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Author Title Type [ Year(Asc)]
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.
R. Milner and Hain, T., Segment-oriented evaluation of speaker diarisation performance, in Proceedings of the 2016 International Conference on Acoustic, Speech and Signal Processing (ICASSP), Shanghai, China, 2016.
P. Lanchantin, Gales, M. J. F., Karanasou, P., Liu, X., Qian, Y., Wang, L., Woodland, P. C., and Zhang, C., Selection of Multi-genre Broadcast Data for the Training of Automatic Speech Recognition Systems, in Proc. ICASSP, 2016.
R. W. M. Ng, Nicolao, M., Saz, O., Hasan, M., Chettri, B., Doulaty, M., Lee, T., and Hain, T., Sheffield LRE 2015 System Description}, in {Odyssey: The Speaker and Language Recognition Workshop (Submitted)}, 2016.
Y. Liu, Fox, C., Hasan, M., and Hain, T., The Sheffield Wargame Corpus - Day Two and Day Three, in Proceedings of Interspeech 2016, San Francisco, USA, 2016.
L. Lu and Renals, S., Small-footprint Deep Neural Networks with Highway Connections for Speech Recognition, in Proc. INTERSPEECH, 2016.
C. Valentini-Botinhao, Wang, X., Takaki, S., and Yamagishi, J., Speech Enhancement for a Noise-Robust Text-to-Speech Synthesis System using Deep Recurrent Neural Networks, in Proc. Interspeech, San Fransisco, US, 2016.
C. Valentini-Botinhao, Wang, X., Takaki, S., and Yamagishi, J., Speech Enhancement for a Noise-Robust Text-to-Speech Synthesis System using Deep Recurrent Neural Networks, in Proceedings of Interspeech 2016, 2016, pp. 352–356.
J. Yang, Zhang, C., Ragni, A., Gales, M. J. F., and Woodland, P. C., System Combiantion with Log-linear Models, in Proc. ICASSP'16, Shanghai, China, 2016.
S. Ronanki, Henter, G. Eje, Wu, Z., and King, S., A template-based approach for speech synthesis intonation generation using LSTMs, in Proc. Interspeech, San Francisco, CA, 2016.
R. Dall, Brognaux, S., Richmond, K., Valentini-Botinhao, C., Henter, G. Eje, Hirschberg, J., Yamagishi, J., and King, S., Testing the consistency assumption: Pronunciation variant forced alignment in read and spontaneous speech synthesis, in Proc. ICASSP, Shanghai, China, 2016, vol. 41.
L. Lu, Zhang, X., and Renais, S., On training the recurrent neural network encoder-decoder for large vocabulary end-to-end speech recognition, in Proc. ICASSP, 2016.
T. Hain, Christian, J., Saz, O., Deena, S., Hasan, M., Ng, R. W. M., Milner, R., Doulaty, M., and Liu, Y., webASR 2 - Improved cloud based speech technology, in Proceedings of the 17th Annual Conference of the International Speech Communication Association (Interspeech), San Francisco, CA, 2016.
2015
R. Milner, Saz, O., Deena, S., Doulaty, M., Ng, R., and Hain, T., The 2015 Sheffield System for Longitudinal Diarisation of Broadcast Media, in {Proceedings of the 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)}, Scottsdale, AZ, 2015.
O. Saz, Doulaty, M., Deena, S., Milner, R., Ng, R., Hasan, M., Liu, Y., and Hain, T., The 2015 Sheffield System for Transcription of Multi–Genre Broadcast Media, in {Proceedings of the 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)}, Scottsdale, AZ, 2015.
M. Wester, Valentini-Botinhao, C., and Henter, G. Eje, Are we using enough listeners? No! An empirically-supported critique of Interspeech 2014 TTS evaluations, in Proc. of Interspeech, Dresden, 2015.
M. Wester, Aylett, M., Tomalin, M., and Dall, R., Artificial Personality and Disfluency, in Proc. of Interspeech, Dresden, 2015.
T. Merritt, Latorre, J., and King, S., Attributing modelling errors in HMM synthesis by stepping gradually from natural to modelled speech, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, 2015.
P. C. Woodland, Liu, X., Qian, Y., Zhang, C., Gales, M. J. F., Karanasou, P., Lanchantin, P., and Wang, L., Cambridge University Transcription Systems for the Multi-Genre Broadcast Challenge, in Proc. of ASRU, Scottsdale, USA, 2015.
P. Bell and Renals, S., Complementary tasks for context-dependent deep neural network acoustic models, in Proc. Interspeech, 2015.
M. Doulaty, Saz, O., and Hain, T., Data-selective Transfer Learning for Multi-Domain Speech Recognition, in Proceedings of the 16th Annual Conference of the International Speech Communication Association (Interspeech), Dresden, Germany, 2015.
L. - H. Chen, Raitio, T., Valentini-Botinhao, C., Ling, Z., and Yamagishi, J., A Deep Generative Architecture for Postfiltering in Statistical Parametric Speech Synthesis, Audio, Speech, and Language Processing, IEEE/ACM Transactions on, vol. 23, pp. 2003-2014, 2015.
T. Merritt, Yamagishi, J., Wu, Z., Watts, O., and King, S., Deep neural network context embeddings for model selection in rich-context HMM synthesis, in Proc. Interspeech, Dresden, Germany, 2015, pp. 2207–2211.
Z. Wu, Valentini-Botinhao, C., Watts, O., and King, S., Deep neural networks employing multi-task learning and stacked bottleneck features for speech synthesis, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2015.
P. Swietojanski and Renals, S., Differentiable Pooling for Unsupervised Speaker Adaptation, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2015.

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