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LOT summer school Ultrasound, phonetics, phonology: Articulation for Beginners!

LOT summer school Ultrasound, phonetics, phonology: Articulation for Beginners!. With special thanks to collaborators Jane Stuart-Smith & Eleanor Lawson Joanne Cleland & Zoe Roxburgh Natasha Zharkova , Laura Black, Steve Cowen Reenu Punnoose , Koen Sebreghts
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LOT summer schoolUltrasound, phonetics, phonology: Articulation for Beginners!With special thanks to collaboratorsJane Stuart-Smith & Eleanor LawsonJoanne Cleland & Zoe RoxburghNatasha Zharkova, Laura Black, Steve CowenReenuPunnoose, KoenSebreghtsSonja Schaeffler & Ineke MennenConnyHeydeAlan Wrench (aka Articulate Instruments Ltd) for AAA software and UTI hardware Various funding – thank you to ESRC, EPSRC, QMU June 2013James M ScobbieCASL Research CentreIntroduction to articulation
  • Brief overview of techniques
  • Ultrasound tongue imaging
  • Playtime
  • Technical issues and the nitty gritty of data
  • Maybe a linguistic illustration
  • Malayalam liquids
  • StructureDifferent laboratories have different solutions
  • Exemplification will be based around current practice at QMU / Articulate Instruments Ltd
  • Topics (mostly in this order)
  • Resolution, fixed aspect ratio representations
  • Up, down and horizontal…the bite plane
  • Quick averaging multiple tongue surfaces
  • Statistical testing of difference between averages
  • Two tongues, synching, de-interfacing
  • Video-rate vs. (ultra) high speed ultrasound
  • Technical issuesMore echo-pulse beams / scanlines means more resolution in a circumferential direction
  • Let’s assume 1 scanline each 2° (180 in a circle)
  • Scanlines get further apart the further they are from the probe
  • At 90mm from probe centre, resolution is 3.14mm
  • At 60mm, resolution is 2mm
  • 45mm it is 1.6mm
  • To maintain these resolutions…
  • A 90° field of view would need 46 scanlines
  • A 135° field of view would need 69 scanlines
  • Spatial resolution around the curveMore sample points means more resolution in a radial direction
  • 8cm depth with 256 sample points = 0.3mm/point
  • Assuming enough pixels to represent each point
  • Spatial resolution along the radii150 s-lines @ 0.9°, FoV 135°, 57fps 50 s-lines @ 2.7°, FoV 135°, 166fps The fan shape is presented on a rectangular screen, and occupies a proportion of that space
  • A TV image has a certain number of data points horizontal / vertical (e.g. in NTSC)
  • These are digitised into pixels at a given resolution…
  • Horizonatal in the head is not the same thing as being parallel to the x-axis in the rectangle!
  • Rectangular imagesApproximate location of EMA coils in analysis of /u/ fronting in SSBEHarrington, Kleber & Reubold 2011Approximate location of EMA coils in analysis of /u/ fronting in SSBE – 2-4mm back/below /i/Harrington et alExample of a UTI vowel space, rotated to occlusal bite plane, with average curves (± 1sd)
  • Left pane is standard view, right the UTI view…
  • UTI single SSE speakerUse a “bite plate” to detect the unique occlusal plane for each speaker, as in typical in EMA
  • Flat plane defined on upper dentition surface
  • Also provides common origin as well as axes
  • Scobbie, Lawson, Cowen, Cleland & Wrench (2012) ms. – I might be able to put this online…
  • Finding the “horizontal”In humans, the directions "rostral" and "caudal" often become confused with anterior and posterior, or superior and inferior. The difference between the two is most easily visualized when looking at the head, as can be seen in the image to the right. From the most caudal of positions in the nervous system (of a person) to a nearby, rostral area, it is equally accurate to say the area in question is rostral as to say it is superior. However, in the frontal lobes of the telencephalon, to say an area is rostral to a nearby area is equivalent to saying it is anterior. Those two lines lie on planes perpendicular to one another. This occurs, as becomes clear in the diagram, due to the intuitive yet curious curving "C" shape of rostrocaudal directionality when discussing the human brain.wikipediabite plateOcclusalbiteplane traceSix young adult female speakers
  • Varying slopes (mean 18.5°)
  • Varying vertical offset
  • Varyinghorizontal offset
  • back of plateVariation in bite planeMean hard palate trace (black) and biteplane trace grey), automatic curve fittingOverlay of 6 hard palatesNormalised (translation and rotation) to rear of bite plane and relocation of origin (+45mm)
  • Better palate trace alignment, with one “rogue”
  • Palates normalised to bite planesPalates can be used to orientate between sessions, by swallowing (e.g. water or yoghurt)
  • Longitudinal, within-speaker
  • Just line up the palates!
  • Easy, huh?!
  • Cross-speaker
  • Might be better than bite plate when worrying about close approximation constrictions
  • Bite plate might be better for open approximation
  • The probe can be moved instead
  • A consistent articulation can be used, eg [u]
  • AlternativesMRI data is collected supine – does it matter?
  • Upright L and supine R “pop” vowel
  • Wrench et al 2011
  • Upright / supine6 female speakers, varied accents
  • 5 reps of pep and of pop in randomised list of vowels
  • 4 blocks, repeating upright/supine set twice
  • Upright first for 3, supine first for 3
  • Pharyngeal slump under gravity of about 3mm
  • And a couple of cases of blade raising
  • SummaryAveraging tokens within-speakerAveraging along 42 fan-grid radii, “parallel” to scan-lines / echo-pulse beam from the probeAveraging within AAAn tokens along radius rTokens of [s] from /si/vs. a different conditionTokens of [s] from /sa/ and /si/t-test of the difference between mean tongue contour at crossing point at each fan line
  • 2-tailed test assuming unequal variances and unequal sample sizes
  • No Bonferroni or other corrections
  • Up to 5 or 6 adjacent radii, mean distance from probe is correlated, perhaps indicating non-independence of such “close” measures
  • For a linguistic interpretation of difference, 5 or 6 adjacent radii, all at p<0.05 on t-test is more important than p<0.0001 on one radius
  • 2 groups of curves2 speakers, 4 frames each
  • 42 radii per speaker…
  • What % of correlations between two random radii are significant, depending on the distance between them
  • Radial distance
  • Grand mean
  • All parts of tongue pooled
  • More cases of adjacent than longdistancecomparisons
  • Pilot correlation v1A range of 9 varied tongue shapes (9 single frames) from each speaker
  • 4 samples for each frame – roughly equally spaced
  • Is there a correlation for fans 10 apart?
  • 9? 8? 7? …
  • Pilot B (NI1)
  • Pilot correlation v23 attempts – more long-distance significance found
  • One sectoron the fan is 7fanlines
  • Just two sample points per frame, front and back?
  • Pilot 2 A = 9 fans rather than 8 were significant (n=18 observations, so lower values of r were significant)
  • Or one in the middlelooking forwards and backwards?
  • Or use many more target types?
  • Or ones that show more subtle differences, such as a set of CV transitions, including every frame, not just varied targets
  • What to try next?Raw tongue curves againTokens of [s] from /sa/ and /si/Significant root advancement (~5mm) and palatalisation (~4mm) in /si/
  • More than 5 adjacent fans where p<0.05, but in 2 areas
  • Mean /sa/ vs. /si/SS-ANOVA best fit lines (∓ 95% c.i.) - DavidsonMean /sa/ vs. /si/Exploring treating >5 fan lines at p<0.05 as categorically “significant” but quantifying it all:
  • Including crossing/pivot points
  • Ignore significance if curves are low confidence
  • Quantify length of the significant tongue surface
  • Estimate total difference in area
  • Mean /sa/ vs. /si/Thick lines for means – cf overlap, non overlap, and crossingsSingle speaker (SSE) Neutral spaceWrench & Scobbie (2006) list some of the problems with video-ultrasound resulting from buffering multiple probe scans into one image
  • More than one scan from the probe in an image
  • Partial scans from the probe in an image
  • Don’t forget 30fps is about 33ms, so synch is vague
  • Some solutions,
  • Use raw probe data (cine loop) but this costs €
  • Use a high scan rate (more than twice NTSC) and then deinterlace the video to 60fps
  • Halves vertical spatial resolution (rectangular up)
  • The two tongue problemThe scanner scans and makes screen imagesVideo digital capture & bufferingThe scanner scans and makes screen imagesVideo digital capture & bufferingIn these images, two apparent tongues show the effect of two scans in the same buffer, on odd and even video “lines”Plain 30fps videoDeinterlace video images to 30fps (16ms or so)
  • “Cineloop” digital output can be stored locally on US scanners
  • Full rectangular cine images
  • Approx 15 second chunks
  • Continuous audio recordings need post-processing alignment
  • AAA / QM Ultrasonix-based system
  • Data stored as raw probe echo-pulse returns
  • Synchronised at source with audio at each frame
  • Video channel freed up, and can be used to capture lip videos
  • Solutions76 scan lines, 100fps, FoV 112°High speed39 scan lines, 196fps, FoV 112°Ultra-high speed25 scan lines, 306fps, FoV 112°Ultra-high speedgɔdback fronttime“dog” – ultra high speed 382fpshs-UTI @ 382fps & video @ 60fps, 300ms
  • Constriction-tracking, comparable to but different to flesh-point tracking
  • “tongue blade height” during [d]Video demo, deinterlaced lip camera 60fps [folder]
  • UTI old dutch and labialised english r [link]
  • Lip ultrax kids [link] – deinterlaced ring [link]
  • High speed UTI 100fps
  • Malayalam retroflex lateral [folder]
  • Slomo [link]
  • Slomo with spline [link]
  • Real speed with spline [link]
  • Demo videosTwo darker (tongue root) liquids, L /ɭ/and R /r/
  • Three clearer (ATR, ~pal’ised) l /l/, r /ɾ/, 5 zh
  • Single frame targetsMalayalam trill /r/ R between /a/
  • Left = closing half of gesture
  • Right = opening half
  • Note trill motion in blade and stable root
  • High speed (100fps)Malayalam tap /ɾ/ between /a/
  • Note greater movement in root, pivot point
  • High speed (100fps)Malayalam retroflex flap /ɭ/
  • Stable root, mobile blade, slower approach with very fast release (nb some UTI artefacts) of over 400mm/sec peak velocity
  • High speed (100fps)Unlike EMA, it’s hard to quantify kinematics
  • Need to explore / compare with EMA
  • Gestural speedPositional examinations are easier
  • Retroflex flap and trill both have a very stable root, which could be due to
  • Posterior bracing to enable the anterior movement
  • Coincidental, because the context was /a__a/ and these liquids have a dark resonance in Malayalam
  • We can compare /a__a/ to /a__i/
  • Root stability?Green = prevvowels andformation ofmaximally retracted “target” (black)
  • Red = duringthe flap
  • Purple = afterwards
  • Retroflex lateral flap in a__aGreen = prevvowels andformation ofmaximally retracted “target” (black)
  • Red = duringthe flap
  • Purple = afterwards
  • High spatial accuracy when orthogonal to beamLower spatial accuracy when parallel to beamRetroflex lateral flap /ɭ/ in a__iOverlap:during period from target toacoustic transition
  • dark aLa
  • light aLi
  • How should weto quantify?
  • No sig differenceanteriorly but…?
  • Comparison Two darker (tongue root) liquids, L /ɭ/and R /r/
  • Three clearer (ATR, ~pal’ised) l /l/, r /ɾ/, 5 zh
  • Single frame targetsTwo darker (tongue root) liquids, L /ɭ/and R /r/
  • Root advancement and some palatalisation
  • Next to an /i/ vowel Three clearer (ATR, ~pal’ised) l /l/, r /ɾ/, 5 zh
  • Root advancement and more palatalisation
  • Next to an /i/ vowel Support for Punnoose’s acoustic findings of dark vs. light resonances in the liquid system,
  • Tongue root
  • Palatal dorsal area
  • Apparent tongue-root bracing for trill and retroflex lateral flap in an /a_a/ context is associated with these being dark consonants
  • There is steady dynamic root coarticulation in /a_i/
  • Both light and dark liquids coarticulate but don’t overlap
  • SummaryAny time for any more?Ultrasound misses a great deal of information!
  • ULTRAX project to obtain corpus of 12 speakers in MRI / UTIto build real-time model
  • Renals& Richmond @ CSTR
  • ULTRAX – adding missing piecesCould be used for head-movement correction within the midsagittal plane and/or
  • Analysis of lip kinematics
  • Headset-mounted cameraEstimate based on oval model of internal 2D labial aperture, 60fps (~17ms per frame)Coronal “cross-sectional area”Measures of curviness of the tongue may escape the image-orientations problem
  • Mielke’s concavity & Zharkova’s dorsal bulge (and others) offer speaker-internal unoriented analysis
  • But there is a worry about front/back of tongue being needed, since end-points can be arbitrary
  • Orientation-free measuresFor a variety of work, it is nice to compare a speaker’s productions against a kind of norm
  • ULTRAX group 1 corpus of 30 children offer useful dataset
  • ata, iti, oto vs. aka, iki, oko
  • Speaker-internal ratio of /k/-/t/, along fanlines
  • Should show extra dorsal distance in /k/ and extra alveolar distance for /t/
  • How do /t/ and /k/ differ?For example, /k/-/t/ of /a/ can be averaged by lining up the maximum excursion point
  • These are not tongue surfaces! Nor in a fan!
  • resultsResults – anterior to left
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