Limited interaction in speech production: Chronometric, speech error, and neuropsychological evidence

Abstract

Results from chronometric and speech errors studies provide convergent evidence for both lower and upper bounds on interaction within the speech production system. Some degree of cascading activation is required to account for patterns of speech errors in neurologically intact and impaired speakers as well as the results of recent chronometric studies. However, the strength of this form of interaction must be limited to account for the occurrence of selective deficits in the production system and restrictions on the conditions under which interactive effects influence reaction times. Similarly, some amount of feedback from phonological to word-level representations is necessary to account for patterns of speech errors in neurologically intact and impaired individuals as well as the influence of phonological neighbours on response latency. This interactive mechanism must also be limited to account for restrictions on the types of speech errors produced following selective deficits within the production system. Results from a variety of empirical traditions therefore converge on the same conclusion: interaction is present, but it must be crucially limited.

Acknowledgment

Preparation of this paper was supported in part by National Institute of Health grants R01 MH-64733, R01 HD21011, and R01 MH66089, and National Science Foundation grant BCS 0213270.

Notes

¹More recent studies (see Indefrey & Levelt, 2004, for a recent review) have utilised neuroimaging techniques to examine word production. This review, however, is limited to speech error and chronometric data (for discussion of neuroimaging evidence specifically concerning the interaction between speech production processes, see de Zubicaray, Wilson, McMahon, & Muthiah, 2001).

²Assuming a single level of lexical representation leads one to attribute the effects of homophonic primes to overlapping phonological, not lexical, representations. It is generally assumed that homophones have distinct lexical representations at some level in the processing system (Bonin & Fayol, 2002; Caramazza, Bi, Costa, & Miozzo, 2004; Caramazza, Costa, Miozzo, & Bi, 2001; Dell, 1990; Jescheniak & Levelt, 1994; Jescheniak, Meyer, & Levelt, 2003; Levelt et al., 1999). Assuming a single lexical level means that homophones share no lexical representation; their only overlap is at the phonological level.

³It is possible that errors such as blends reflect the simultaneous selection of multiple representations (e.g., Levelt et al., 1999).

⁴As noted by Vigliocco and Hartsuiker (2002): footnote 8), del Viso et al.'s (1991) claim that their data do not show a mixed error bias is debatable. del Viso et al. did find a significant mixed error effect in their overall corpus. However, the effect was carried by a small subset of highly similar items; when these were excluded no significant mixed error effect was found. Although this subset analysis is justifiable (the mixed error effect should not be carried by only a few items), it may in fact be too conservative (obscuring a true mixed error effect).

⁵To guard against strategic effects, Ferreira & Griffin discouraged participants from covertly completing each sentence by including a condition where pictures were never an appropriate sentence completion (Experiment 3). Effects of similar magnitude were observed here, arguing against a strategic basis for the findings.

⁶The ‘Cascading Feedforward Account’ simulation of Rapp & Goldrick (2000) was used. With the exception of the L-level jolt (which was varied as described above), parameters were set at the default levels described in that paper.

⁷The ‘Restricted Interaction Account’ simulation of Rapp & Goldrick (2000) was used. Parameter settings that deviated from default settings were: feedforward connections were set to 0.05; L-level jolt was set to 5.0; and feedback connections were varied as specified above.

⁸Limited feedback predicts that some formal errors should be produced with sufficiently high levels of L-level damage. The pattern of performance exhibited by EA (Shelton & Weinrich, 1997) is consistent with this prediction.

⁹Related mechanisms can produce similar effects within attractor-based systems (Plaut & Shallice, 1993).

¹⁰Of course, the phoneme will enter into feedback loops with some L-level units (e.g., <ZIP>); however, these units are more distant from the target and thus will receive less feedback support from the target (e.g., <HAT> will receive support from the /ae/ and /t/ of target ‘cat’).

¹¹Note that lexical frequency is highly correlated with other lexical properties such as age of acquisition (for recent reviews, see Bonin, Barry, Méot, & Chalard, 2004; Zevin & Seidenberg, 2002).

¹²This feedback would have similar consequences in systems with unitary lexical semantic representations and those with distributed feature representations. In the former, the activation of a single unit would be enhanced, making it a stronger competitor for selection at the lexical semantic level. In the latter, a set of semantic features would have their activation enhanced, allowing their corresponding lexical concept to compete more strongly for selection.

¹³Note that Bonin and Fayol (2002) found a reverse frequency effect in a picture categorisation task (e.g., pictures with low frequency names were more quickly categorised than those with high frequency names).

¹⁴The ‘High Interaction Account’ simulation of Rapp & Goldrick (2000) was used. Parameter settings that deviated from default settings were: feedforward and feedback connections were set to 0.05 (except when varied as specified above); and the L-level jolt was set to 5.0.

¹⁵Note that these restrictions on interaction are not a priori features of production theories. Plaut and Shallice (1993) proposed a theory of (semantically based) reading without strict selection points. In a similar context, Van Orden and colleagues (Farrar & Van Orden, 2001; Van Orden, op de Haar, & Bosman, 1997) have proposed that interactions can occur between non-adjacent representational levels.

Additional information

Notes on contributors

Matthew Goldrick

Correspondence should be addressed to Matthew Goldrick, Department of Linguistics, Northwestern University, Evanston, IL, 60208, USA. [email protected]