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Registration
Become an mngu0 member to access the articulatory data
Rugchatjaroen (2014)
A. Rugchatjaroen. Articulatory-Based English Consonant Synthesis in 2-D Digital Waveguide Mesh. PhD thesis, Department of Electronics, University of York, ...
Cai et al. (2014)
M.-Q. Cai, Z.-H. Ling, and L.-R. Dai. Formant-controlled speech synthesis using hidden trajectory model. In Proc. Interspeech, pages 1529–1533, Singapore, ...
A. Rugchatjaroen and D. M. Howard. Flexibility of cosine impedance function in 2-d digital waveguide mesh for plosive synthesis. In Signal and Information ...
Z. Wu, K. Zhao, X. Wu, X. Lan, and H. Meng. Acoustic to articulatory mapping with deep neural network. Multimedia Tools and Applications, pages 1–19, 2014.
Mumtaz et al. (2014)
R. Mumtaz, S. Preuss, C. Neuschaefer-Rube, C. Hey, R. Sader, and P. Birkholz. Tongue contour reconstruction from optical and electrical palatography. Signal ...
Cai et al. (2012)
M.-Q. Cai, Z.-H. Ling, and L.-R. Dai. Target-filtering model based articulatory movement prediction for articulatory control of HMM-based speech synthesis. In ...
Ben Youssef et al. (2014)
A. Ben Youssef, H. Shimodaira, and D. Braude. Speech driven talking head from estimated articulatory features. In Proc. ICASSP, pages 4606–4610, Florence, ...
Ben Youssef et al. (2013)
A. Ben Youssef, H. Shimodaira, and D. A. Braude. Articulatory features for speech-driven head motion synthesis. In Proc. Interspeech, Lyon, France, August ...
Steiner (2010)
I. M. A. Steiner. Observations on the dynamic control of an articulatory synthesizer using speech production data. PhD thesis, Saarland University, ...
Richmond et al. (2013)
K. Richmond, Z. Ling, J. Yamagishi, and B. Uría. On the evaluation of inversion mapping performance in the acoustic domain. In Proc. Interspeech, Lyon, France, ...
Steiner et al. (2013)
I. Steiner, K. Richmond, and S. Ouni. Speech animation using electromagnetic articulography as motion capture data. In Proc. 12th International Conference on ...
Zhao et al. (2013)
K. Zhao, Z. Wu, and L. Cai. A real-time speech driven talking avatar based on deep neural network. In Signal and Information Processing Association Annual ...
Canevari et al. (2013)
C. Canevari, L. Badino, L. Fadiga, and G. Metta. Cross-corpus and cross-linguistic evaluation of a speaker-dependent DNN-HMM ASR system using EMA data. In ...
Steiner et al. (2012)
I. Steiner, K. Richmond, and S. Ouni. Using multimodal speech production data to evaluate articulatory animation for audiovisual speech synthesis. In 3rd ...
symbol lists available
Files made available for download to describe the symbols used in the day1 labelling
s1 normalisation parameters
Means and standard deviations for S1 data processing released
all publications
A list of all publications in all categories
Z. Ling, K. Richmond, and J. Yamagishi. Articulatory control of HMM-based parametric speech synthesis using feature-space-switched multiple regression. IEEE ...
Uria et al. (2012)
Benigno Uria, Iain Murray, Steve Renals, and Korin Richmond. Deep architectures for articulatory inversion. In Proc. Interspeech, Portland, Oregon, USA, ...
Ling, Richmond & Yamagishi (2012)
Zhen-Hua Ling, Korin Richmond, and Junichi Yamagishi. Vowel creation by articulatory control in HMM-based parametric speech synthesis. In Proc. Interspeech, ...
Richmond and Renals (2012)
Korin Richmond and Steve Renals. Ultrax: An animated midsagittal vocal tract display for speech therapy. In Proc. Interspeech, Portland, Oregon, USA, September ...
mngu0 corpus
mgnu0 comprises several data modalities
Dental casts in preparation
3D scans of mngu0 dental casts to be released soon
3D Dental Scan
Screenshot of 3D scan of mngu0 dental casts
Richmond (2009)
K. Richmond. "Preliminary inversion mapping results with a new EMA corpus." In Proc. Interspeech, pages 2835–2838, Brighton, UK, September 2009.
MRI data now available
The raw mngu0 MRI data is now available for download from this site
Zhao et al. (2010)
Tian-Yi Zhao, Zhen-Hua Ling, Ming Lei, Li-Rong Dai and Qing-Feng Liu. "Minimum generation error training for HMM-based prediction of articulatory movements." ...
Uria et al. (2011)
B. Uria, S. Renals and K. Richmond. "A deep neural network for acoustic-articulatory speech inversion." In NIPS 2011 Workshop on Deep Learning and Unsupervised ...
Steiner et al. (2012)
I. Steiner, K. Richmond, I. Marshall, and C. D. Gray. The magnetic resonance imaging subset of the mngu0 articulatory corpus. Journal of the Acoustical ...