Comparing tongue shapes from ultrasound imaging using smoothing spline analysis of variance.

Ultrasound imaging of the tongue is increasingly common in speech production research. However, there has been little standardization regarding the quantification and statistical analysis of ultrasound data. In linguistic studies, researchers may want to determine whether the tongue shape for an articulation under two different conditions (e.g., consonants in word-final versus word-medial position) is the same or different. This paper demonstrates how the smoothing spline ANOVA (SS ANOVA) can be applied to the comparison of tongue curves [Gu, Smoothing Spline ANOVA Models (Springer, New York, 2002)]. The SS ANOVA is a technique for determining whether or not there are significant differences between the smoothing splines that are the best fits for two data sets being compared. If the interaction term of the SS ANOVA model is statistically significant, then the groups have different shapes. Since the interaction may be significant even if only a small section of the curves are different (i.e., the tongue root is the same, but the tip of one group is raised), Bayesian confidence intervals are used to determine which sections of the curves are statistically different. SS ANOVAs are illustrated with some data comparing obstruents produced in word-final and word-medial coda position.

[1]  G. Wahba Smoothing noisy data with spline functions , 1975 .

[2]  P. Ladefoged,et al.  Factor analysis of tongue shapes. , 1971, Journal of the Acoustical Society of America.

[3]  Peter Craven,et al.  Smoothing noisy data with spline functions , 1978 .

[4]  G. Wahba Bayesian "Confidence Intervals" for the Cross-validated Smoothing Spline , 1983 .

[5]  M. C. Jones,et al.  Spline Smoothing and Nonparametric Regression. , 1989 .

[6]  G. Wahba Spline models for observational data , 1990 .

[7]  Raymond D. Kent,et al.  X‐ray microbeam speech production database , 1990 .

[8]  M H Cohen,et al.  Electromagnetic midsagittal articulometer systems for transducing speech articulatory movements. , 1992, The Journal of the Acoustical Society of America.

[9]  L. Raphael,et al.  Cross-sectional tongue shape and linguopalatal contact patterns in [s], [∫], [f], and [1] , 1992 .

[10]  G. Wahba,et al.  Smoothing Spline ANOVA with Component-Wise Bayesian “Confidence Intervals” , 1993 .

[11]  W. Hardcastle,et al.  Diagnosis and therapy of abnormal alveolar stops in a speech-disordered child using electropalatography , 1993 .

[12]  B. Silverman,et al.  Nonparametric Regression and Generalized Linear Models: A roughness penalty approach , 1993 .

[13]  G. Wahba,et al.  Semiparametric Analysis of Variance with Tensor Product Thin Plate Splines , 1993 .

[14]  B. Silverman,et al.  Nonparametric regression and generalized linear models , 1994 .

[15]  B. Silverman,et al.  Nonparametric Regression and Generalized Linear Models: A roughness penalty approach , 1993 .

[16]  G. Wahba,et al.  Smoothing spline ANOVA for exponential families, with application to the Wisconsin Epidemiological Study of Diabetic Retinopathy : the 1994 Neyman Memorial Lecture , 1995 .

[17]  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.

[18]  G Papcun,et al.  Two cross-linguistic factors underlying tongue shapes for vowels. , 1996, The Journal of the Acoustical Society of America.

[19]  M. Stone,et al.  Three-dimensional tongue surface shapes of English consonants and vowels. , 1996, The Journal of the Acoustical Society of America.

[20]  V. Gracco,et al.  Functional data analyses of lip motion. , 1996, The Journal of the Acoustical Society of America.

[21]  P. Foulkes The Sounds of the World's Languages , 1997 .

[22]  Grace Wahba,et al.  Spatial-Temporal Analysis of Temperature Using Smoothing Spline ANOVA , 1998 .

[23]  P. Hoole,et al.  On the lingual organization of the German vowel system. , 1999, The Journal of the Acoustical Society of America.

[24]  W S Levine,et al.  Modeling tongue surface contours from Cine-MRI images. , 2001, Journal of speech, language, and hearing research : JSLHR.

[25]  Bryan Gick,et al.  The use of ultrasound for linguistic phonetic fieldwork , 2002, Journal of the International Phonetic Association.

[26]  Paul J. Smith,et al.  Principal Components Representation of the Two-Dimensional Coronal Tongue Surface , 2002, Phonetica.

[27]  Yuedong Wang,et al.  Shape‐Invariant Modeling of Circadian Rhythms with Random Effects and Smoothing Spline ANOVA Decompositions , 2003, Biometrics.

[28]  B. Gick,et al.  Speech habilitation of hard of hearing adolescents using electropalatography and ultrasound as evaluated by trained listeners , 2003, Clinical linguistics & phonetics.

[29]  H. Ombao,et al.  Smoothing Spline ANOVA for Time-Dependent Spectral Analysis , 2003 .

[30]  P. Rubin,et al.  CASY: The Haskins Configurable Articulatory Synthesizer , 2003 .

[31]  Lisa Davidson Addressing phonological questions with ultrasound , 2005, Clinical linguistics & phonetics.

[32]  Alexei Kochetov,et al.  Syllable position effects and gestural organization: Articulatory evidence from Russian , 2005 .

[33]  C. Kambhamettu,et al.  Automatic contour tracking in ultrasound images , 2005, Clinical linguistics & phonetics.

[34]  R. Gilbert,et al.  Quantitative three‐dimensional ultrasound analysis of tongue protrusion, grooving and symmetry: Data from 12 normal speakers and a partial glossectomee , 2005, Clinical linguistics & phonetics.

[35]  M. Stone A guide to analysing tongue motion from ultrasound images , 2005, Clinical linguistics & phonetics.

[36]  Khalil Iskarous,et al.  Patterns of tongue movement , 2005, J. Phonetics.