1 The phonetics of speech errors Frisch, S. A. University of South Florida This work supported by NIH-NIDCD R

2 Study of Speech Errors The study of how speech can go wrong in speech errors tells us something about how the speech production mechanism works Error patterns are not “random” Similar approach used in (non-clinical) aphasia research: The disordered brain tells us about normal brain function

3 Phonological Segment Errors Many speech errors involve the apparent mis-production of a single phoneme For example, “Frisch fry” for ‘fish fry’ “like box” for ‘bike locks’

4 One Model Dell (1986 inter alia) spreading activation model –Word nodes activate phonemes –Phonemes activate related words, creating competition –The model is also noisy –Accidental over-activation of an incorrect phoneme creates a speech error

5 Support for the Model Increased speech error rate when phonemic context is shared in experiments that elicit errors For example, initial /b, m/ errors –Most common: make bake –Less common: made bake –Least common: mad bake

6 More Support Errors that create words are more common than errors that don’t –For example, sip zap vs. sung zone Also, effect of word level can be influenced by processing time –Demand for a quick response results in less of a lexical effect –Not enough time for competition to build

7 Errors at the Gestural Level Sub-phonemic errors have not been studied much Mowrey & MacKay (1990) used electrodes to examine muscle activation in errors, and found evidence for frequent “gradient” errors Pouplier (2003) EMA study found gestural insertion common in errors

8 Research Program Is the gestural level just another interactive layer in the connectionist model, or a separate component? Is gestural activation and competition like phonemic/lexical activation and competition? Can lexical influences on gestural errors be found?

9 Frisch & Wright (2002) Acoustic study of speech errors between /s/ and /z/ –Crucially differ in voicing (periodicity) –Less crucial differences in amplitude and duration –However, some potential interdependence of these differences

10 Categorical Gestures Errors that switched all the way to the ‘norm’ of the other category were more common than extreme gradient errors Clearer to see for /s/ targets than for /z/ targets, as devoicing of /z/ is phonetically normal

11 Distribution of voicing /s//z/ 0% % % % %13252

12 Current research Speech errors studied using ultrasound Ultrasound recordings give a means to directly measure articulation Similar to Pouplier (2003) EMA studies

13 Participants Four undergraduate students from the CSD department Monolingual English speakers No self-reported history of speech/hearing disorder

14 Procedure Participant seated in head stabilizing apparatus Ultrasound probe held under chin by a cross bar Compressible acoustically transparent standoff between chin and probe Participant produces six repetitions of each tongue twister Stimuli read off of a printed sheet

15 Stimuli Four word tongue twisters designed to elicit stop onset errors –Tongue twisters focusing on onset segments used to increase error rate –Error patterns in tongue twisters similar to error patterns in comparable spontaneous speech (Shattuck-Hufnagel 1992)

16 Stimuli Baseline recordings of productions of a speech sound by a participant e.g. “ta tae tae ta” –Determine normal patterns for /t, d, k, g/ –48 productions of each onset (2 stimuli with 4 onsets repeated 6 times) –Measure tongue blade and dorsum raising

17 Stimuli Experimental recordings of stimuli with alternations e.g. “cop tab top cab” e.g. “ka tae ta kae” –Six word stimuli, eight non-word stimuli –Measure tongue blade angle and dorsum raising –Compare with normal patterns –Look for abnormalities

18 Measures Dorsum raising measure –Direction of dorsum raising varies by vowel (Wodzinski 2004) –Typical direction of dorsum raising determined from baseline –Distance of dorsum raising along typical direction measured for each stimulus (both velar and alveolar)

19 Measures Tongue blade angle –Elevation of the tongue tip/blade measured as an angle –Line segment drawn over last 1 cm of visible tongue tip –Angle of elevation measured from proximal point to distal point (0 is level, positive is inclined, negative is declined)

20 “normal” alveolar

21 Results so far Both categorical and gradient errors observed Small perturbations from baseline values commonly observed in tongue twisters Are perturbations gradient errors? –Ordinary coarticulation vs. –“Traces” of activation of intended target (Goldrick 2004)

22 Representative participant Alveolar targetsVelar targets

23 “normal” /t//t/ with dorsum raised An apparent gradient error from / g / gesture intrusion

24 Representative participant Alveolar targetsVelar targets Not a gradient error… a vowel error… produced / ge /

25 Discussion Gradient errors confirmed in a more natural production task than Pouplier (2003) Categorical errors appear to be much more common Error data difficult to quantify –“Normal” alveolars in alternating context produced differently than in baseline –Difference not found in velars

26 Gestural activation Findings are consistent with a model of error production as erroneous gestural activation –Competing articulators may be simultaneously activated, producing an abnormal combination –Activation can be partial and not total, and so not accounted for by a completely symbolic linguistic model

27 Gestural activation Prevalence of categorical errors –For the most part, however, erroneous activation of gestures falls into the normal phonetic categories –Consistent with gestural level as another level of the hierarchy –Activation of coordinated combinations is supported by segment and word level activation

28 Lexical effects? Error rates higher in nonword case But no obvious tendency for more gradient or categorical errors in one case or the other Emphasizes need to quantify data

29 Representative participant Alveolar targetsVelar targets

30 Conclusions Making progress… –While this study does not address many of the long-term questions of the research program, it is generating valuable basic data on speech errors –Even this relatively simple study has illuminated many challenges to the study of gestural speech errors within the speech production system