7.REFERENCES

[1]King，S.，et al.2007.Speech production knowledge in automatic speech recognition.J.Acoust.Soc.Am.，121（2）：p.723-742.

[2]Badin，P.，et al.2010.Can you ‘read’ tongue movements？ Evaluation of the contribution of tongue display to speech understanding.Speech Communication，52（6）：p.493-503.

[3]Youssef，A.B.，et al.2011.Towards a multi-speaker visual articulatory feedback system，in InterSpeech2011.p.589-592.

[4]Lewis，J.1991.Automated lip-sync：Background and techniques.The Journal of Visualization and Computer Animation，2（4）：p.118-122.

[5]Bregler，C.，Covell，M.and Slaney，M.1997.Video rewrite：Driving visual speech with audio，in the 24th annual conference on Computer graphics and interactive techniques.p.353-360.

[6]Hofer，G.and Richmond，K.2010.Comparison of HMM and TMDN methods for lip synchronisation，in InterSpeech2010.

[7]Schroeter，J.and Sondhi，M.M.1992.Speech coding based on physiological models of speech production，in Advances in Speech Signal Processing，S.Furui and M.M.Sondhi，Editors.Marcel Dekker Inc.：New York.p.231-268.

[8]Atal，B.S.，et al.1978.Inversion of articulatory-to-acoustic transformation in the vocal tract by a computer-sorting technique.J.Acoust.Soc.Am.，63（5）：p.1535-1555.

[9]Ouni，S.and Laprie，Y.2005 Modeling the articulatory space using a hypercube codebook for acoustic-to-articulatory inversion.J.Acoust.Soc.Am.，118（1）：p.444-460.

[10]Schroeter，J.and Sondhi，M.M.1994.Techniques for estimating vocal-tract shapes from the speech signal.IEEE Trans.Speech Audio Processing，2：p.133-150.

[11]Roweis，S.，Data driven production models for speech processing.1999，California Institute of Technology.

[12]Hiroya，S.and Honda，M.2004.Estimation of Articulatory Movements from Speech Acoustics Using an HMM-Based Speech Production Model.IEEE Transactions on Speech and Audio Processing，12（2）：p.175-185.

[13]Zhang，L.and Renals，S.2008.Acoustic-articulatory modeling with the trajectory HMM.IEEE Signal Process Letter，15：p.245-248.

[14]Ling，Z.，Richmond，K.and Yamagishi，J.2010.An Analysis of HMM-based prediction of articulatory movements.Speech Communication，52（10）：p.834-846.

[15]Katsamanis，A.，Papandreou，G.and Maragos，P.2009.Face active appearance modeling and speech acoustic information to recover articulation.IEEE Trans.Acoust.，Speech，and Language Processing，17（3）：p.411-422.

[16]Dusan，S.2000.Statistical estimation of articulatory trajectories from the speech signal using dynamical and phonological constraints，in Dept.of Electrical and Computer Engineering.University of Waterloo.

[17]Toutios，A.and Margaritis，K.2008.Contribution to statistical acoustic-to-EMA mapping，in InterSpeech2008.

[18]Toda，T.，Black，A.W.and Tokuda，K.2008.Statistical mapping between articulatory movements and acoustic spectrum using a Gaussian mixture model.Speech Communication，50：p.215-227.

[19]Hogden，J.，et al.1996.Accurate recovery of articulator positions from acoustics：New conclusions based on human data.J.Acoust.Soc.Am.，100：p.1819-1834.

[20]Papcun，G.，et al.1992.Inferring articulation and recognising gestures from acoustics with a neural network trained on X-ray microbeam data.J.Acoust.Soc.Am.，92（2）：p.688-700.

[21]Richmond，K.2002.Estimating articulatory parameters from the acoustic speech signal.University of Edinburgh.

[22]Uría，B.，et al.2012.Deep Architectures for Articulatory Inversion，in InterSpeech2012.

[23]Wu，Z.，et al.2015.Acoustic to articulatory mapping with deep neural network.Multi med Tools Appl，74（22）：p.9889-9907.

[24]Richmond，K.2007.Trajectory mixture density networks with multiple mixtures for acoustic-articulatory inversion，in Lecture Notes in Computer Science，M.Chetouani，et al.，Editors.Springer-Verlag Berlin.p.263-272.

[25]Toutios，A.and Ouni，S.2011.Predicting tongue positions from acoustics and facial features，in InterSpeech2011.p.2661-2664.

[26]Ioffe，S.and Szegedy，C.2015.Batch Normalization：Accelerating Deep Network Training by Reducing Internal Covariate Shift，in the 32nd International Conference on Machine Learning.

[27]Richmond，K.2006.A trajectory mixture density network for the acoustic-articulatory inversion mapping，in InterSpeech2006.p.577-580.

FANG Qiang PhD He is an associate professor of Institute of Linguistics，Chinese Academy of Social Sciences.His research interests include speech production and modeling.

E-mail：fangqiang@cass.org.cn

方强 中国社会科学院语言研究所，副研究员研究兴趣包括言语产生机理研究、发音建模研究、言语工程等

E-mail：fangqiang@cass.org.cn