Bryan Gick and I recently published an article on “Gait Change in Tongue Movement” in Scientific Reports (Nature Publishing Group). Below is the abstract, with images alongside. However, if you want an easy-to-follow walkthrough of the paper, I also published a YouTube video on the paper on my YouTube Channel for Maps of Speech.

During locomotion, humans switch gaits from walking to running, and horses from walking to trotting to cantering to galloping, as they increase their movement rate. It is unknown whether gait change leading to a wider movement rate range is limited to locomotive-type behaviours, or instead is a general property of any rate-varying motor system. The tongue during speech provides a motor system that can address this gap. In controlled speech experiments, using phrases containing complex tongue-movement sequences, we demonstrate distinct gaits in tongue movement at different speech rates. As speakers widen their tongue-front displacement range, they gain access to wider speech-rate ranges.

At the widest displacement ranges, speakers also produce categorically different patterns for their slowest and fastest speech. Speakers with the narrowest tongue-front displacement ranges show one stable speech-gait pattern, and speakers with widest ranges show two. Critical fluctuation analysis of tongue motion over the time-course of speech revealed these speakers used greater effort at the beginning of phrases—such end-state-comfort effects indicate speech planning.

Based on these findings, we expect that categorical motion solutions may emerge in any motor system, providing that system with access to wider movement-rate ranges.

Jia Ying, Jason A. Shaw, Christopher Carignan, Michael Proctor, myself, and Catherine T. Best just published Evidence for active control of tongue lateralization in Australian English /l/. Most research on /l/ articulation has looked at motion timing along the midline, or midsagittal plane. This study compares that information to motion on the sides of the tongue. It focuses on Australian English (AusE), using three-dimensional electromagnetic articulography (3D EMA).

The articulatory analyses show: 1) consistent with past work, the timing lag between mid-sagittal tongue tip and tongue body gestures differs for syllable onsets and codas, and for different vowels.

2) The lateral channel is formed by tilting the tongue to the left/right side of the oral cavity as opposed to curving the tongue within the coronal plane

3) the timing of lateral channel formation relative to the tongue body gesture is consistent across syllable positions and vowel contexts – even though temporal lag between tongue tip and tongue body gestures varies.

This last result suggests that lateral channel formation is actively controlled as opposed to resulting as a passive consequence of tongue stretching. These results are interpreted as evidence that the formation of the lateral channel is a primary articulatory goal of /l/ production in AusE.

Patrycja Strycharczuk, Jason Shaw, and I just published Locating de-lateralization in the pathway of sound changes affecting coda /l/, in which we analyze New Zealand English /l/ using Ultrasound and Articulometry. You can find the article here. Put in the simplest English terms, the article shows the process by which /l/-sounds in speech can change over time from a light /l/ (like the first /l/ in ‘lull’) to a darker /l/ (like the second /l/ in ‘lull’). This darkening is the result of the upper-back, or dorsum, of the tongue moving closer to the back of the throat. This motion in turn reduces lateralization, or the lowering of the sides of the tongue away from the upper teeth. This is followed, over time, by the tongue tip no longer connecting to the front of the hard palate – the /l/ becomes a back vowel or vocalizes.

If you want a more technical description, Here is the abstract:

‘Vocalization’ is a label commonly used to describe an ongoing change in progress affecting coda /l/ in multiple accents of English. The label is directly linked to the loss of consonantal constriction observed in this process, but it also implicitly signals a specific type of change affecting manner of articulation from consonant to vowel, which involves loss of tongue lateralization, the defining property of lateral sounds. In this study, we consider two potential diachronic pathways of change: an abrupt loss of lateralization which follows from the loss of apical constriction, versus slower gradual loss of lateralization that tracks the articulatory changes to the dorsal component of /l/. We present articulatory data from seven speakers of New Zealand English, acquired using a combination of midsagittal and lateral EMA, as well as midsagittal ultrasound. Different stages of sound change are reconstructed through synchronic variation between light, dark, and vocalized /l/, induced by systematic manipulation of the segmental and morphosyntactic environment, and complemented by comparison of different individual articulatory strategies. Our data show a systematic reduction in lateralization that is conditioned by increasing degrees of /l/-darkening and /l/-vocalization. This observation supports the idea of a gradual diachronic shift and the following pathway of change: /l/-darkening, driven by the dorsal gesture, precipitates some loss of lateralization, which is followed by loss of the apical gesture. This pathway indicates that loss of lateralization is an integral component in the changes in manner of articulation of /l/ from consonantal to vocalic.

In 2013, I recorded 11 North American English speakers, each reading eight phrases with two flaps in two syllables (e.g “We have editor books”), and at 5 speech rates, from about 3 syllables/second to 7 syllables/second. Each recording included audio, ultrasound imaging of the tongue, and articulometry.

The dataset has taken a truly inordinate amount of time to label, transcribe (thank you Romain Fiasson), rotate, align ultrasound to audio, fit in shared time (what is known as a Procrustean fit), extract acoustic correlates, and clean from tokens that have recording or unfixable alignment errors.

It is, however, now 2019 and I have a cleaned dataset. I’ve uploaded the dataset, with data at each point of processing included, to an Open Science Framework website: I will, over the next few weeks, upload documentation on how I processed the data, as well as videos of the cleaned data showing ultrasound and EMA motion.

By September 1st, I plan on submitting a research article discussing the techniques used to build the dataset, as well as theoretically motivated subset of the articulatory to acoustic correlates within this dataset to a special issue of a journal whose name I will disclose should they accept the article for publication.

This research was funded by a Marsden Grant from New Zealand, “Saving energy vs. making yourself understood during speech production”. Thanks to Mark Tiede for writing the quaternion rotation tools needed to oriented EMA traces, and to Christian Kroos for teaching our group at Western Sydney Universiy how to implement them. Thanks to Michael Proctor for building filtering and sample repair tools for EMA traces. Thanks also to Wei-rong Chen for writing the palate estimation tool needed to replace erroneous palate traces. Special thanks to Scott Lloyd for his part in developing and building the ultrasound transducer holder prototype used in this research. Dedicated to the memory of Roman Fiasson, who completed most of the labelling and transcription for this project.

Katie Bicevskis, Bryan Gick, and I recently published “Visual-tactile Speech Perception and the Autism Quotient” in Frontiers in Communication: Language Sciences. In this article, we demonstrated that the more people self-describe as having autistic-spectrum traits, the more they tolerate a separation of time between air-flow hitting the skin and lip opening from a video of someone saying an ambiguous “ba” or “pa” when identifying the syllable they saw and felt, but did not hear.

First, in an earlier publication, we showed that visual-tactile speech integration depended on this alignment of lip opening and airflow, and that this is evidence of modality-neutral speech primitives. We use whatever information we have during speech perception regardless of whether we see, feel, or hear it.

This result is best illustrated with the image above. The image shows a kind of topographical map, where white represents the “mountaintop” of people saying the ambiguous audio-tactile syllable is a “pa”, and green represents the “valley” of people saying the ambiguous audio-tactile syllable is a “ba”. On the X-axis is the alignment of the onset of air-flow release and lip opening. On the Y-axis is the participants’ Autism-spectrum Quotient. Lower numbers represent people who describe themselves as having the least autistic-like traits; the most neurotypical. At the bottom of the scale, perceivers identify the ambiguous syllables as “pa” with as much as 70-75% likelihood when the air-flow arrived 100-150 milliseconds after lip opening – about when it would arrive if a speaker stood 30-45 cm away from the perceiver. Deviations led to steep dropoffs, where perceivers would identify the syllable as “pa” only 20-30% of the time if the air flow arrived 300 milliseconds before the lip opening. In contrast, at the top of the AQ scale, perceivers reported perceiving “pa” as little as only 5% more often when audio-tactile alignment was closer to that experienced in typical speech.

These results are very similar what happens with people who are on the autism spectrum with audio-visual speech. Autists listen to speech with their ears more than they look with their eyes, showing a weak multisensory coherence during perceptual tasks (Happé and Frith, 2006). Our results suggest such weak coherence extends into the neutoryipcal population, and can be measured in tasks where the sensory modalities are well-balanced (which is easier to do in speech when audio is removed.)

References:

Bicevskis, K., Derrick, D., and Gick, B. (2016). Visual-tactile integration in speech perception: Evidence for modality neutral speech primitives. Journal of the Acoustical Society of America, 140(5):3531–3539

Derrick, D., Bicevskis, K., and Gick, B. (2019). Visual-tactile speech perception and the autism quotient. Frontiers in Communication – Language Sciences, 3(61):1–11

Derrick, D., Anderson, P., Gick, B., and Green, S. (2009). Characteristics of air puffs produced in English ‘pa’: Experiments and simulations. Journal of the Acoustical Society of America, 125(4):2272–2281

Happé, F., and Frith, U. (2006). The Weak Coherence Account: Detail-focused Cognitive Style in Autism Spectrum Disorders. Journal of Autism and Developmental Disorders, 36(1):5-25

Katie Bicevskis, Bryan Gick, and I just had “Visual-tactile Speech Perception and the Autism Quotient” – our reexamination and expansion our evidence for ecologically valid visual-tactile speech perception – accepted to Frontiers in Communications: Language Sciences.  Right now only the abstract and introductory parts are online, but the whole article will be up soon.  The major contribution of this article is  that speech perceivers integrate air flow information during visual speech perception with greater reliance upon event-related accuracy the more they self-describe as neurotypical.  This behaviour supports the Happé & Frith (2006) weak coherence account of Autism Spectrum Disorder.  Put very simply, neurotypical people perceive whole events, but people with ASD perceive uni-sensory parts of events, often with greater detail than their neurotypical counterparts.  This account partially explains how autists can have deficiencies in imagination and social skills, but also be extremely capable in other areas of inquiry.  Previous models of ASD offered an explanation of disability, Happé and Frith offer an explanation of different ability.

I will be expanding on this discussion, with a plain English explanation of the results, once the article is fully published.  For now, the article abstract is re-posted here:

“Multisensory information is integrated asymmetrically in speech perception: An audio signal can follow video by 240 milliseconds, but can precede video by only 60 ms, without disrupting the sense of synchronicity (Munhall et al., 1996). Similarly, air flow can follow either audio (Gick et al., 2010) or video (Bicevskis et al., 2016) by a much larger margin than it can precede either while remaining perceptually synchronous. These asymmetric windows of integration have been attributed to the physical properties of the signals; light travels faster than sound (Munhall et al., 1996), and sound travels faster than air flow (Gick et al., 2010). Perceptual windows of integration narrow during development (Hillock-Dunn and Wallace, 2012), but remain wider among people with autism (Wallace and Stevenson, 2014). Here we show that, even among neurotypical adult perceivers, visual-tactile windows of integration are wider and flatter the higher the participant’s Autism Quotient (AQ) (Baron-Cohen et al, 2001), a self-report screening test for Autism Spectrum Disorder (ASD). As ‘pa’ is produced with a tiny burst of aspiration (Derrick et al., 2009), we applied light and inaudible air puffs to participants’ necks while they watched silent videos of a person saying ‘ba’ or ‘pa’, with puffs presented both synchronously and at varying degrees of asynchrony relative to the recorded plosive release burst, which itself is time-aligned to visible lip opening. All syllables seen along with cutaneous air puffs were more likely to be perceived as ‘pa’. Syllables were perceived as ‘pa’ most often when the air puff occurred 50-100 ms after lip opening, with decaying probability as asynchrony increased. Integration was less dependent on time-alignment the higher the participant’s AQ. Perceivers integrate event-relevant tactile information in visual speech perception with greater reliance upon event-related accuracy the more they self-describe as neurotypical, supporting the Happé & Frith (2006) weak coherence account of ASD.”

This is a guide to the use of ultrasound and EMA in combination.  It is a bit out of date, and probably needs a day or two of work to make fully correct, but it describes the techniques I use with 3 researchers.  Of course I wrote this years ago, and now I can run an Ultrasound/EMA experiment by myself if I need to.