Analysis of speech production real-time MRI
暂无分享,去创建一个
Shrikanth S. Narayanan | Vikram Ramanarayanan | Louis Goldstein | Sam Tilsen | Michael I. Proctor | Krishna S. Nayak | Johannes Töger | K. Nayak | L. Goldstein | M. Proctor | Vikram Ramanarayanan | Sam Tilsen | J. Töger
[1] P. Toutouzas,et al. A Magnetic Resonance Imaging Study , 2003 .
[2] Olov Engwall. From real-time MRI to 3d tongue movements , 2004, INTERSPEECH.
[3] M H Cohen,et al. Electromagnetic midsagittal articulometer systems for transducing speech articulatory movements. , 1992, The Journal of the Acoustical Society of America.
[4] M Stone,et al. A head and transducer support system for making ultrasound images of tongue/jaw movement. , 1995, The Journal of the Acoustical Society of America.
[5] Jorge Baptista,et al. Computational Processing of the Portuguese Language , 2012, Lecture Notes in Computer Science.
[6] C. C. Goodyear,et al. Measurements of vocal tract shapes using magnetic resonance imaging , 1992 .
[7] Florian Metze,et al. A flexible stream architecture for ASR using articulatory features , 2002, INTERSPEECH.
[8] Rafael De Assuncao Sampaio,et al. Vocal Tract Morphology Using Real-Time Magnetic Resonance Imaging , 2017, 2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI).
[9] Dani Byrd,et al. The elastic phrase: modeling the dynamics of boundary-adjacent lengthening , 2003, J. Phonetics.
[10] Jens Frahm,et al. High-speed real-time magnetic resonance imaging of fast tongue movements in elite horn players. , 2015, Quantitative imaging in medicine and surgery.
[11] Marie-Odile Berger,et al. A guided approach for automatic segmentation and modeling of the vocal tract in MRI images , 2011, 2011 19th European Signal Processing Conference.
[12] Shrikanth Narayanan,et al. Are Articulatory Settings Mechanically Advantageous for Speech Motor Control? , 2014, PloS one.
[13] Stefanie Wuhrer,et al. A hybrid approach to 3d tongue modeling from vocal tract MRI using unsupervised image segmentation and mesh deformation , 2014, INTERSPEECH.
[14] Tao Li,et al. The Relationships Among Various Nonnegative Matrix Factorization Methods for Clustering , 2006, Sixth International Conference on Data Mining (ICDM'06).
[15] Chunming Li,et al. Distance Regularized Level Set Evolution and Its Application to Image Segmentation , 2010, IEEE Transactions on Image Processing.
[16] P. Mermelstein. Articulatory model for the study of speech production. , 1973, The Journal of the Acoustical Society of America.
[17] Zhi-Pei Liang,et al. High-resolution dynamic speech imaging with deformation estimation , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[18] Li Deng,et al. Variational inference and learning for segmental switching state space models of hidden speech dynamics , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..
[19] Zhi-Pei Liang,et al. High‐resolution dynamic speech imaging with joint low‐rank and sparsity constraints , 2015, Magnetic resonance in medicine.
[20] Daniel Carey,et al. Vocal Tract Images Reveal Neural Representations of Sensorimotor Transformation During Speech Imitation , 2017, Cerebral cortex.
[21] Geoffrey J. Gordon,et al. A Unified View of Matrix Factorization Models , 2008, ECML/PKDD.
[22] P. W. Nye,et al. Analysis of vocal tract shape and dimensions using magnetic resonance imaging: vowels. , 1991, The Journal of the Acoustical Society of America.
[23] Shrikanth S. Narayanan,et al. Convex Hull Convolutive Non-Negative Matrix Factorization for Uncovering Temporal Patterns in Multivariate Time-Series Data , 2016, INTERSPEECH.
[24] Alan A Wrench,et al. A MULTI-CHANNEL/MULTI-SPEAKER ARTICULATORY DATABASE FOR CONTINUOUS SPEECH RECOGNITION RESEARCH , 2000 .
[25] R. Boubertakh,et al. Towards clinical assessment of velopharyngeal closure using MRI: evaluation of real-time MRI sequences at 1.5 and 3 T. , 2012, The British journal of radiology.
[26] Shrikanth S. Narayanan,et al. Spatio-temporal articulatory movement primitives during speech production: extraction, interpretation, and validation. , 2013, The Journal of the Acoustical Society of America.
[27] Shrikanth Narayanan,et al. Temporal analysis of articulatory speech errors using direct image analysis of real time magnetic resonance imaging. , 2010 .
[28] Li Deng,et al. Target-directed mixture dynamic models for spontaneous speech recognition , 2004, IEEE Transactions on Speech and Audio Processing.
[29] P. Birkholz. Modeling Consonant-Vowel Coarticulation for Articulatory Speech Synthesis , 2013, PloS one.
[30] H. Barnhart,et al. The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions , 2015, Statistical methods in medical research.
[31] P. Ladefoged,et al. Factor analysis of tongue shapes. , 1971, Journal of the Acoustical Society of America.
[32] Maureen Stone,et al. A head and transducer support system for making ultrasound images of tongue/jaw movement. , 1994 .
[33] António J. S. Teixeira,et al. Quantitative systematic analysis of vocal tract data , 2016, Comput. Speech Lang..
[34] R. Schweizer,et al. On the Physiology of Normal Swallowing as Revealed by Magnetic Resonance Imaging in Real Time , 2014, Gastroenterology research and practice.
[35] S. Maeda. An articulatory model of the tongue based on a statistical analysis , 1979 .
[36] Shrikanth S. Narayanan,et al. On Short-Time Estimation of Vocal Tract Length from Formant Frequencies , 2015, PloS one.
[37] Shrikanth S. Narayanan,et al. Characterizing Post-Glossectomy Speech Using Real-time MRI , 2013 .
[38] Shrikanth S. Narayanan,et al. Articulation of English vowels in running speech: A real-time MRI study , 2015, ICPhS.
[39] Shrikanth S. Narayanan,et al. Sensitivity of Quantitative RT-MRI Metrics of Vocal Tract Dynamics to Image Reconstruction Settings , 2016, INTERSPEECH.
[40] S. Giszter,et al. A Neural Basis for Motor Primitives in the Spinal Cord , 2010, The Journal of Neuroscience.
[41] Will Grathwohl,et al. Using digital ultrasound to investigate trill vibration. , 2010 .
[42] Shrikanth S. Narayanan,et al. Investigating articulatory setting - pauses, ready position, and rest - using real-time MRI , 2010, INTERSPEECH.
[43] Shrikanth S. Narayanan,et al. A subject-independent acoustic-to-articulatory inversion , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[44] António J. S. Teixeira,et al. Unsupervised segmentation of the vocal tract from real-time MRI sequences , 2015, Comput. Speech Lang..
[45] Shrikanth S. Narayanan,et al. Directly data-derived articulatory gesture-like representations retain discriminatory information about phone categories , 2016, Comput. Speech Lang..
[46] Michael Proctor,et al. Articulatory bases of sonority in English liquids , 2012 .
[47] Shrikanth Narayanan,et al. Automatic speech recognition using articulatory features from subject-independent acoustic-to-articulatory inversion. , 2011, The Journal of the Acoustical Society of America.
[48] Tzyy-Ping Jung,et al. Deriving gestural score from articulator-movement records using weighted temporal decomposition , 1996, IEEE Trans. Speech Audio Process..
[49] A I Pack,et al. Magnetic resonance imaging of the upper airway structure of children with obstructive sleep apnea syndrome. , 2001, American journal of respiratory and critical care medicine.
[50] Li Deng,et al. Production models as a structural basis for automatic speech recognition , 1997, Speech Commun..
[51] Shrikanth S. Narayanan,et al. Exploiting speech production information for automatic speech and speaker modeling and recognition - possibilities and new opportunities , 2012, Proceedings of The 2012 Asia Pacific Signal and Information Processing Association Annual Summit and Conference.
[52] Shrikanth Narayanan,et al. Paralinguistic mechanisms of production in human "beatboxing": a real-time magnetic resonance imaging study. , 2013, The Journal of the Acoustical Society of America.
[53] Timothy F. Cootes,et al. Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[54] Didier Demolin,et al. Coarticulation and articulatory compensations studied by dynamic MRI , 1997, EUROSPEECH.
[55] Didier Demolin,et al. REAL TIME MRI AND ARTICULATORY COORDINATIONS IN VOWELS , 2000 .
[56] W. Fitch,et al. Morphology and development of the human vocal tract: a study using magnetic resonance imaging. , 1999, The Journal of the Acoustical Society of America.
[57] Shrikanth Narayanan,et al. Interspeaker variability in hard palate morphology and vowel production. , 2013, Journal of speech, language, and hearing research : JSLHR.
[58] S. Ohman. Numerical model of coarticulation. , 1967, The Journal of the Acoustical Society of America.
[59] Shrikanth S. Narayanan,et al. Emphatic segments and emphasis spread in Lebanese Arabic: a Real-time Magnetic Resonance Imaging Study , 2012, INTERSPEECH.
[60] Shrikanth Narayanan,et al. Real-time magnetic resonance imaging and electromagnetic articulography database for speech production research (TC). , 2014, The Journal of the Acoustical Society of America.
[61] Pascal Spincemaille,et al. Anticipatory Posturing of the Vocal Tract Reveals Dissociation of Speech Movement Plans from Linguistic Units , 2016, PloS one.
[62] LiChunming,et al. Distance regularized level set evolution and its application to image segmentation , 2010 .
[63] Shrikanth S. Narayanan,et al. Enhanced airway-tissue boundary segmentation for real-time magnetic resonance imaging data , 2014 .
[64] Shrikanth S. Narayanan,et al. Timing effects of syllable structure and stress on nasals: A real-time MRI examination , 2009, J. Phonetics.
[65] António J. S. Teixeira,et al. Real-Time MRI for Portuguese - Database, Methods and Applications , 2012, PROPOR.
[66] Robert Sader,et al. Dynamic near‐real‐time magnetic resonance imaging for analyzing the velopharyngeal closure in comparison with videofluoroscopy , 2004, Journal of magnetic resonance imaging : JMRI.
[67] Zhi-Pei Liang,et al. The role of the pharynx and tongue in enhancement of vowel nasalization: a real-time MRI investigation of French nasal vowels , 2013, INTERSPEECH.
[68] Herbert Gish,et al. A parametric approach to vocal tract length normalization , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.
[69] Andrew D Scott,et al. Adaptive averaging applied to dynamic imaging of the soft palate , 2013, Magnetic resonance in medicine.
[70] Shrikanth S. Narayanan,et al. Improved imaging of lingual articulation using real‐time multislice MRI , 2012, Journal of magnetic resonance imaging : JMRI.
[71] J D Subtelny,et al. Cineradiographic study of sibilants. , 1972, Folia phoniatrica.
[72] Athanasios Katsamanis,et al. Validating rt-MRI Based Articulatory Representations via Articulatory Recognition , 2011, INTERSPEECH.
[73] W S Levine,et al. Modeling tongue surface contours from Cine-MRI images. , 2001, Journal of speech, language, and hearing research : JSLHR.
[74] Steffen E. Petersen,et al. Comparison of Cartesian and Non-Cartesian Real-Time MRI Sequences at 1.5T to Assess Velar Motion and Velopharyngeal Closure during Speech , 2016, PloS one.
[75] Louis Goldstein,et al. Automatic Analysis of Singleton and Geminate Consonant Articulation Using Real-Time Magnetic Resonance Imaging , 2011, INTERSPEECH.
[76] K. Nimkin,et al. Feasibility study to assess clinical applications of 3-T cine MRI coupled with synchronous audio recording during speech in evaluation of velopharyngeal insufficiency in children , 2015, Pediatric Radiology.
[77] Li Lee,et al. A frequency warping approach to speaker normalization , 1998, IEEE Trans. Speech Audio Process..
[78] C. Drissi,et al. Feasibility of dynamic MRI for evaluating velopharyngeal insufficiency in children , 2011, European Radiology.
[79] Dani Byrd,et al. Articulatory comparison of Tamil liquids and stops using real‐time magnetic resonance imaging. , 2009 .
[80] Yang Wang,et al. Extraction of tongue contour in real-time magnetic resonance imaging sequences , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[81] Ravi Seethamraju,et al. Faster dynamic imaging of speech with field inhomogeneity corrected spiral fast low angle shot (FLASH) at 3 T , 2010, Journal of magnetic resonance imaging : JMRI.
[82] Louis Goldstein,et al. Dynamics and articulatory phonology , 1996 .
[83] Chris H. Q. Ding,et al. Convex and Semi-Nonnegative Matrix Factorizations , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[84] Raymond D. Kent,et al. Development of vocal tract length during early childhood: a magnetic resonance imaging study. , 2005, The Journal of the Acoustical Society of America.
[85] Hermann Ney,et al. Speaker adaptive modeling by vocal tract normalization , 2002, IEEE Trans. Speech Audio Process..
[86] Jayaram K. Udupa,et al. Automatic segmentation of vocal tract MR images , 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.
[87] Simon King,et al. ASR - articulatory speech recognition , 2001, INTERSPEECH.
[88] Bishnu S. Atal,et al. Efficient coding of LPC parameters by temporal decomposition , 1983, ICASSP.
[89] Athanasios Katsamanis,et al. Automatic Data-Driven Learning of Articulatory Primitives from Real-Time MRI Data Using Convolutive NMF with Sparseness Constraints , 2011, INTERSPEECH.
[90] Shrikanth S. Narayanan,et al. Statistical methods for estimation of direct and differential kinematics of the vocal tract , 2013, Speech Commun..
[91] Keiichi Tokuda,et al. Mapping from articulatory movements to vocal tract spectrum with Gaussian mixture model for articulatory speech synthesis , 2004, SSW.
[92] Kenneth N. Stevens,et al. On the Derivation of Area Functions and Acoustic Spectra from Cinéradiographic Films of Speech , 1964 .
[93] Shrikanth Narayanan,et al. An approach to real-time magnetic resonance imaging for speech production. , 2003, The Journal of the Acoustical Society of America.
[94] W J Hardcastle,et al. The Use of Electropalatography in Phonetic Research , 1972, Phonetica.
[95] Li Deng,et al. A dynamic, feature-based approach to the interface between phonology and phonetics for speech modeling and recognition , 1998, Speech Commun..
[96] Raymond D. Kent,et al. X‐ray microbeam speech production database , 1990 .
[97] Shrikanth S. Narayanan,et al. Velic coordination in French nasals: a real-time magnetic resonance imaging study , 2013, INTERSPEECH.
[98] Athanasios Katsamanis,et al. Rapid semi-automatic segmentation of real-time magnetic resonance images for parametric vocal tract analysis , 2010, INTERSPEECH.
[99] F. Mussa-Ivaldi. Motor Primitives , Force-Fields and the Equilibrium Point Theory , .
[100] Didier Demolin,et al. Real-time MRI and articulatory coordination in speech. , 2002, Comptes rendus biologies.
[101] M. Echternach,et al. Morphometric Differences of Vocal Tract Articulators in Different Loudness Conditions in Singing , 2016, PloS one.
[102] Katalin Mády,et al. Consonant articulation in glossectomee speech evaluated by dynamic MRI , 2003 .
[103] Audra E. Kosh,et al. Linear Algebra and its Applications , 1992 .
[104] Prasanta Kumar Ghosh,et al. Information theoretic optimal vocal tract region selection from real time magnetic resonance images for broad phonetic class recognition , 2016, Comput. Speech Lang..
[105] T. Flash,et al. When practice leads to co-articulation: the evolution of geometrically defined movement primitives , 2004, Experimental Brain Research.
[106] Reint Geuze,et al. From Basic Motor Control to Functional Recovery , 1999 .
[107] Dani Byrd,et al. Analysis of pausing behavior in spontaneous speech using real-time magnetic resonance imaging of articulation. , 2009, The Journal of the Acoustical Society of America.
[108] D J Ostry,et al. Coarticulation of jaw movements in speech production: is context sensitivity in speech kinematics centrally planned? , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[109] Shrikanth S. Narayanan,et al. Region Segmentation in the Frequency Domain Applied to Upper Airway Real-Time Magnetic Resonance Images , 2009, IEEE Transactions on Medical Imaging.
[110] Raanan Arens,et al. A novel volumetric magnetic resonance imaging paradigm to study upper airway anatomy. , 2002, Sleep.
[111] Athanasios Katsamanis,et al. Statistical multi-stream modeling of real-time MRI articulatory speech data , 2010, INTERSPEECH.
[112] Louis-Jean Boë,et al. Tracking Contours of Orofacial Articulators from Real-Time MRI of Speech , 2016, INTERSPEECH.
[113] Mikkel B. Stegmann,et al. Active appearance models: Theory and cases , 2000 .
[114] Pierre Badin,et al. Collecting and analysing two- and three- dimensional MRI data for Swedish , 1999 .
[115] Shrikanth S. Narayanan,et al. An investigation of articulatory setting using real-time magnetic resonance imaging. , 2013, The Journal of the Acoustical Society of America.
[116] M M Sondhi,et al. The potential role of speech production models in automatic speech recognition. , 1996, The Journal of the Acoustical Society of America.
[117] Roy Santosham,et al. Assessment of swallowing and its disorders-a dynamic MRI study. , 2013, European journal of radiology.
[118] Shrikanth S. Narayanan,et al. Systematic variation in the articulation of the Korean liquid across prosodic positions , 2015, International Congress of Phonetic Sciences.
[119] Peter Ladefoge,et al. Direct Measurement of the Vocal Tract , 1971 .
[120] Shrikanth S. Narayanan,et al. Speaker verification based on the fusion of speech acoustics and inverted articulatory signals , 2016, Comput. Speech Lang..
[121] Peter Birkholz,et al. A Gesture-Based Concept for Speech Movement Control in Articulatory Speech Synthesis , 2007, COST 2102 Workshop.
[122] Shrikanth Narayanan,et al. Automatic identification of stable modes and fluctuations in a repetitive task using real-time MRI , 2007 .
[123] Charles A Conway,et al. Real-Time Magnetic Resonance Imaging of Velopharyngeal Activities with Simultaneous Speech Recordings , 2011, The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association.
[124] Atsushi Nakamura,et al. Production-Oriented Models for Speech Recognition , 2006, IEICE Trans. Inf. Syst..
[125] Eric Vatikiotis-Bateson,et al. The Haskins optically corrected ultrasound system (HOCUS). , 2005, Journal of speech, language, and hearing research : JSLHR.
[126] Demetri Terzopoulos,et al. Snakes: Active contour models , 2004, International Journal of Computer Vision.
[127] Richard A. Harshman,et al. Factor analysis of tongue shapes. , 1971, The Journal of the Acoustical Society of America.
[128] António J. S. Teixeira,et al. Segmentation and Analysis of Vocal Tract from MidSagittal Real-Time MRI , 2013, ICIAR.
[129] Bradley P. Sutton,et al. Using magnetic resonance to image the pharynx during Arabic speech: Static and dynamic aspects , 2012, INTERSPEECH.
[130] Zhi-Pei Liang,et al. High‐frame‐rate full‐vocal‐tract 3D dynamic speech imaging , 2017, Magnetic resonance in medicine.
[131] Engin Erzin,et al. Vocal Tract Airway Tissue Boundary Tracking for rtMRI Using Shape and Appearance Priors , 2017, INTERSPEECH.
[132] Zhen-Hua Ling,et al. Articulatory Control of HMM-Based Parametric Speech Synthesis Using Feature-Space-Switched Multiple Regression , 2013, IEEE Transactions on Audio, Speech, and Language Processing.
[133] Véronique Delvaux,et al. French nasal vowels: acoustic and articulatory properties , 2002, INTERSPEECH.
[134] Timothy F. Cootes,et al. Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..
[135] Shrikanth S. Narayanan,et al. Evaluation of swallow function after tongue cancer treatment using real-time magnetic resonance imaging: a pilot study. , 2013, JAMA otolaryngology-- head & neck surgery.
[136] Shinji Maeda,et al. Compensatory Articulation During Speech: Evidence from the Analysis and Synthesis of Vocal-Tract Shapes Using an Articulatory Model , 1990 .
[137] A I Pack,et al. Identification of craniofacial risk factors for obstructive sleep apnoea using three-dimensional MRI , 2011, European Respiratory Journal.
[138] Shrikanth Narayanan,et al. Articulation of Mandarin Sibilants: a multi-plane realtime MRI study , 2012 .
[139] Pierre Badin,et al. Deriving vocal-tract area functions from midsagittal profiles and formant frequencies: A new model for vowels and fricative consonants based on experimental data , 1995, Speech Commun..
[140] Zhi-Pei Liang,et al. A real-time MRI investigation of the role of lingual and pharyngeal articulation in the production of the nasal vowel system of French , 2015, J. Phonetics.
[141] Shrikanth S. Narayanan,et al. Data-driven analysis of realtime vocal tract MRI using correlated image regions , 2010, INTERSPEECH.
[142] Sidney S. Fels,et al. 3D segmentation of the tongue in MRI: a minimally interactive model-based approach , 2015, Comput. methods Biomech. Biomed. Eng. Imaging Vis..
[143] Peter Birkholz,et al. Articulatory Synthesis of Speech and Singing: State of the Art and Suggestions for Future Research , 2009, COST 2102 School.
[144] C. C. Goodyear,et al. On the use of neural networks in articulatory speech synthesis , 1993 .
[145] Ren-Hua Wang,et al. Integrating Articulatory Features Into HMM-Based Parametric Speech Synthesis , 2009, IEEE Transactions on Audio, Speech, and Language Processing.
[146] Marc E Miquel,et al. Recommendations for real‐time speech MRI , 2016, Journal of magnetic resonance imaging : JMRI.
[147] Jens Frahm,et al. Real‐time MRI of speaking at a resolution of 33 ms: Undersampled radial FLASH with nonlinear inverse reconstruction , 2013, Magnetic resonance in medicine.
[148] I. Jolliffe. Principal Component Analysis , 2002 .
[149] Shrikanth S. Narayanan,et al. Characterizing Articulation in Apraxic Speech Using Real-Time Magnetic Resonance Imaging. , 2017, Journal of speech, language, and hearing research : JSLHR.
[150] Hani Yehia,et al. A parametric three-dimensional model of the vocal-tract based on MRI data , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[151] Gérard Bailly,et al. A three-dimensional linear articulatory model based on MRI data , 1998, ICSLP.
[152] Caitlin Smith. Complex Tongue Shaping in Lateral Liquid Production Without Constriction-Based Goals , 2014 .
[153] Jens Frahm,et al. Real‐time magnetic resonance imaging of normal swallowing , 2012, Journal of magnetic resonance imaging : JMRI.