The Centre for Speech Technology Research, The university of Edinburgh

Publications by Cassia Valentini-Botinhao

[1] Rasmus Dall, Sandrine Brognaux, Korin Richmond, Cassia Valentini-Botinhao, Gustav Eje Henter, Julia Hirschberg, and Junichi Yamagishi. Testing the consistency assumption: pronunciation variant forced alignment in read and spontaneous speech synthesis. In Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pages 5155-5159, March 2016. [ bib | .pdf | Abstract ]
[2] Yan Tang, Martin Cooke, and Cassia Valentini-Botinhao. Evaluating the predictions of objective intelligibility metrics for modified and synthetic speech. Computer Speech & Language, 35:73 - 92, 2016. [ bib | DOI | Abstract ]
[3] Cassia Valentini-Botinhao, Markus Toman, Michael Pucher, Dietmar Schabus, and Junichi Yamagishi. Intelligibility of time-compressed synthetic speech: Compression method and speaking style. Speech Communication, October 2015. [ bib | DOI | Abstract ]
[4] C. Valentini-Botinhao, Z. Wu, and S. King. Towards minimum perceptual error training for DNN-based speech synthesis. In Proc. Interspeech, Dresden, Germany, September 2015. [ bib | .pdf | Abstract ]
[5] M. Pucher, M. Toman, D. Schabus, C. Valentini-Botinhao, J. Yamagishi, B. Zillinger, and E Schmid. Influence of speaker familiarity on blind and visually impaired children's perception of synthetic voices in audio games. In Proc. Interspeech, Dresden, Germany, September 2015. [ bib | .pdf | Abstract ]
[6] Mirjam Wester, Cassia Valentini-Botinhao, and Gustav Eje Henter. Are we using enough listeners? No! An empirically-supported critique of Interspeech 2014 TTS evaluations. In Proc. Interspeech, pages 3476-3480, Dresden, September 2015. [ bib | .pdf | Abstract ]
[7] Z. Wu, C. Valentini-Botinhao, O. Watts, and S. King. Deep neural networks employing multi-task learning and stacked bottleneck features for speech synthesis. In Proc. ICASSP, pages 4460-4464, Brisbane, Australia, April 2015. [ bib | .pdf | Abstract ]
[8] B. Uria, I. Murray, S. Renals, C. Valentini-Botinhao, and J. Bridle. Modelling acoustic feature dependencies with artificial neural networks: Trajectory-RNADE. In Proc. ICASSP, pages 4465-4469, Brisbane, Australia, April 2015. [ bib | .pdf | Abstract ]
[9] Ling-Hui Chen, T. Raitio, C. Valentini-Botinhao, Z. Ling, and J. Yamagishi. A deep generative architecture for postfiltering in statistical parametric speech synthesis. Audio, Speech, and Language Processing, IEEE/ACM Transactions on, 23(11):2003-2014, 2015. [ bib | DOI | Abstract ]
[10] Zhizheng Wu, Cassia Valentini-Botinhao, Oliver Watts, and Simon King. Deep neural network 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. [ bib | .pdf ]
[11] Cassia Valentini-Botinhao, Junichi Yamagishi, and Simon King. Intelligibility enhancement of speech in noise. In Proceedings of the Institute of Acoustics, volume 36, pages 96-103, Birmingham, UK, October 2014. [ bib | .pdf | Abstract ]
[12] C. Valentini-Botinhao and M. Wester. Using linguistic predictability and the Lombard effect to increase the intelligibility of synthetic speech in noise. In Proc. Interspeech, pages 2063-2067, Singapore, September 2014. [ bib | .pdf | Abstract ]
[13] L.-H. Chen, T. Raitio, C. Valentini-Botinhao, J. Yamagishi, and Z.-H. Ling. DNN-Based Stochastic Postfilter for HMM-Based Speech Synthesis. In Proc. Interspeech, pages 1954-1958, Singapore, September 2014. [ bib | .pdf | Abstract ]
[14] C. Valentini-Botinhao, M. Toman, M. Pucher, D. Schabus, and J. Yamagishi. Intelligibility Analysis of Fast Synthesized Speech. In Proc. Interspeech, pages 2922-2926, Singapore, September 2014. [ bib | .pdf | Abstract ]
[15] C. Valentini-Botinhao, J. Yamagishi, S. King, and R. Maia. Intelligibility enhancement of HMM-generated speech in additive noise by modifying mel cepstral coefficients to increase the glimpse proportion. Computer Speech and Language, 28(2):665-686, 2014. [ bib | DOI | .pdf | Abstract ]
[16] C. Valentini-Botinhao, J. Yamagishi, S. King, and Y. Stylianou. Combining perceptually-motivated spectral shaping with loudness and duration modification for intelligibility enhancement of HMM-based synthetic speech in noise. In Proc. Interspeech, Lyon, France, August 2013. [ bib | .pdf ]
[17] M. Cooke, C. Mayo, and C. Valentini-Botinhao. Intelligibility-enhancing speech modifications: the Hurricane Challenge. In Proc. Interspeech, Lyon, France, August 2013. [ bib | .pdf ]
[18] Cassia Valentini-Botinhao, Mirjam Wester, Junichi Yamagishi, and Simon King. Using neighbourhood density and selective SNR boosting to increase the intelligibility of synthetic speech in noise. In 8th ISCA Workshop on Speech Synthesis, pages 133-138, Barcelona, Spain, August 2013. [ bib | .pdf | Abstract ]
[19] C. Valentini-Botinhao, E. Godoy, Y. Stylianou, B. Sauert, S. King, and J. Yamagishi. Improving intelligibility in noise of HMM-generated speech via noise-dependent and -independent methods. In Proc. ICASSP, Vancouver, Canada, May 2013. [ bib | .pdf ]
[20] Cassia Valentini-Botinhao. Intelligibility enhancement of synthetic speech in noise. PhD thesis, University of Edinburgh, 2013. [ bib | .pdf | Abstract ]
[21] Y. Tang, M. Cooke, and C. Valentini-Botinhao. A distortion-weighted glimpse-based intelligibility metric for modified and synthetic speech. In Proc. SPIN, 2013. [ bib | .pdf ]
[22] M. Cooke, C. Mayo, C. Valentini-Botinhao, Y. Stylianou, B. Sauert, and Y. Tang. Evaluating the intelligibility benefit of speech modifications in known noise conditions. Speech Communication, 55:572-585, 2013. [ bib | .pdf | Abstract ]
[23] C. Valentini-Botinhao, J. Yamagishi, and S. King. Evaluating speech intelligibility enhancement for HMM-based synthetic speech in noise. In Proc. Sapa Workshop, Portland, USA, September 2012. [ bib | .pdf | Abstract ]
[24] C. Valentini-Botinhao, S. Degenkolb-Weyers, A. Maier, E. Noeth, U. Eysholdt, and T. Bocklet. Automatic detection of sigmatism in children. In Proc. WOCCI, Portland, USA, September 2012. [ bib | .pdf | Abstract ]
[25] C. Valentini-Botinhao, J. Yamagishi, and S. King. Mel cepstral coefficient modification based on the Glimpse Proportion measure for improving the intelligibility of HMM-generated synthetic speech in noise. In Proc. Interspeech, Portland, USA, September 2012. [ bib | Abstract ]
[26] C. Valentini-Botinhao, J. Yamagishi, and S. King. Using an intelligibility measure to create noise robust cepstral coef´Čücients for HMM-based speech synthesis. In Proc. LISTA Workshop, Edinburgh, UK, May 2012. [ bib | .pdf ]
[27] C. Valentini-Botinhao, R. Maia, J. Yamagishi, S. King, and H. Zen. Cepstral analysis based on the Glimpse proportion measure for improving the intelligibility of HMM-based synthetic speech in noise. In Proc. ICASSP, pages 3997-4000, Kyoto, Japan, March 2012. [ bib | DOI | .pdf | Abstract ]
[28] Cassia Valentini-Botinhao, Junichi Yamagishi, and Simon King. Can objective measures predict the intelligibility of modified HMM-based synthetic speech in noise? In Proc. Interspeech, August 2011. [ bib | .pdf | Abstract ]
[29] Cassia Valentini-Botinhao, Junichi Yamagishi, and Simon King. Evaluation of objective measures for intelligibility prediction of HMM-based synthetic speech in noise. In Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on, pages 5112-5115, May 2011. [ bib | DOI | .pdf | Abstract ]