Cue validity and sentence interpretation in English, German, and Italian

MacWhinney, Brian; Bates, Elizabeth; Kliegl, Reinhold

doi:10.1016/s0022-5371(84)90093-8

Cited by 393 publications

(409 citation statements)

References 20 publications

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“…A limitation of this proposal, however, is that it does not capture the effects of the edit distance to a sentence string with a plausible meaning on people's reliance on syntax. As we have seen here, when the edit distance is relatively large (for example, between an active structure and a passive structure), people tend to interpret the string literally, even if the content is implausible (29). However, when the edit distance between two alternatives is smaller-as in the double-object/prepositional phrase object alternations or the transitive/intransitive alternations-people have a greater tendency to interpret the string according to the more plausible alternative.…”

Section: Discussionmentioning

confidence: 59%

“…The cue integration approach proposed in the competition model (29) is similar in spirit to a noisy-channel model in its assumption of noise in the input and its reliance on the integration of information from a variety of sources. However, the specific cue integration approach proposed in the competition model does not appear to be quite consistent with the observed results.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Rational integration of noisy evidence and prior semantic expectations in sentence interpretation

Gibson

Bergen²,

Piantadosi

2013

Proc. Natl. Acad. Sci. U.S.A.

317

501

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Sentence processing theories typically assume that the input to our language processing mechanisms is an error-free sequence of words. However, this assumption is an oversimplification because noise is present in typical language use (for instance, due to a noisy environment, producer errors, or perceiver errors). A complete theory of human sentence comprehension therefore needs to explain how humans understand language given imperfect input. Indeed, like many cognitive systems, language processing mechanisms may even be "well designed"-in this case for the task of recovering intended meaning from noisy utterances. In particular, comprehension mechanisms may be sensitive to the types of information that an idealized statistical comprehender would be sensitive to. Here, we evaluate four predictions about such a rational (Bayesian) noisy-channel language comprehender in a sentence comprehension task: (i) semantic cues should pull sentence interpretation towards plausible meanings, especially if the wording of the more plausible meaning is close to the observed utterance in terms of the number of edits; (ii) this process should asymmetrically treat insertions and deletions due to the Bayesian "size principle"; such nonliteral interpretation of sentences should (iii) increase with the perceived noise rate of the communicative situation and (iv) decrease if semantically anomalous meanings are more likely to be communicated. These predictions are borne out, strongly suggesting that human language relies on rational statistical inference over a noisy channel.T raditionally, models of sentence comprehension have assumed that the input to the sentence comprehension mechanism is an error-free sequence of words (e.g., refs. 1-6). However, the noise inherent in normal language use-due to producer or perceiver errors-makes this assumption an oversimplification. For example, language producers may misspeak or mistype because they do not have a full command of the language (due to being very young or a nonnative speaker, or suffering from a language disorder like aphasia), because they have not fully planned an utterance in advance, or because they are trying to communicate under the influence of stress or confusion. Similarly, language comprehenders may mishear or misread things because of their own handicaps (e.g., poor hearing/sight, or not paying sufficient attention), because the environment is noisy, or because the producer is not making sufficient effort in communicating clearly (e.g., whispering or mumbling, or writing in sloppy handwriting). Given the prevalence of these noise sources, it is plausible that language processing mechanisms are well adapted to handling noisy input, and so a complete model of language comprehension must allow for the existence of noise.Noisy-channel models (7) of speech perception have been prominent in the literature for many years (e.g., 8-11). Furthermore, several researchers have observed the importance of noise in the input for the compositional, syntactic processes of sentence unders...

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Section: Discussionmentioning

confidence: 59%

Section: Discussionmentioning

confidence: 99%

Rational integration of noisy evidence and prior semantic expectations in sentence interpretation

Gibson

Bergen²,

Piantadosi

2013

Proc. Natl. Acad. Sci. U.S.A.

317

501

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“…In the same task, the children's performance was better than chance if the whole of the sentence was presented. The cross-linguistic data reported by a number of researchers on sentence interpretation (Bates et al, 1982;Kail, 1989;Kilborn & Cooreman, 1987;MacWhinney, Bates, & Kliegl, 1984;McDonald & Heilenman, 1991) are also compatible with this view. Theses authors used a sentence interpretation paradigm in which subjects were required to choose the subject/agen t of a sentence with a structure like (14) (from MacWhinney et al, 1984, p. 139): 14a.…”

Section: Discussionmentioning

confidence: 62%

“…MacWhinney et al (1984) found that Italian speakers relied on agreem ent to make decisions about the subject/agent of the sentence, while English speakers relied overwhelm ingly on word order. Dutch, French and Spanish behave like Italian in this respect: Kilborn and Cooreman (1987) showed that speakers of Dutch rely more on agreement than on word order, and Kail (1989) and McDonald and Heilenman (1991) showed the same for French and Spanish.…”

Section: Discussionmentioning

confidence: 99%

One or More Labels on the Bottles? Notional Concord in Dutch and French

Vigliocco¹,

Hartsuiker²,

Jarema³

et al. 1996

Language and Cognitive Processes

113

119

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“…We have studied the use of these cues in Arabic (Taman, 1993), Bulgarian (Andonova, 1998), Chinese (Bates, Chen, Tzeng, Li, & Opie, 1991;Li, Bates, Liu, & MacWhinney, 1992;Tzeng, Chen, & Hung, 1991), Dutch (Kilborn & Ito, 1989;McDonald, 1986;McDonald, 1987a;McDonald, 1987b), English (Bates, McNew, MacWhinney, Devescovi, & Smith, 1982;MacWhinney & Bates, 1978;MacWhinney, Bates, & Kliegl, 1984), French (Kail, 1989), Hebrew (Sokolov, 1989), Hindi (Vaid & Pandit, 1991), Hungarian MacWhinney, OsmanSági, & Slobin, 1991;MacWhinney & Pléh, 1988;MacWhinney & Pléh, 1997;MacWhinney, Pléh, & Bates, 1985), Italian Bates et al, 1982), Japanese (Kilborn & Ito, 1989;Sasaki, 1994;Sasaki, 1997a;Sasaki, 1997b), Russian (Kempe & MacWhinney, 1998), Spanish (Kail, 1989), Turkish (MacWhinney et al, 1991), and Warlpiri (Bavin & Shopen, 1989).…”

mentioning

confidence: 99%

The competition model: the input, the context, and the brain

MacWhinney¹

2001

Cognition and Second Language Instruction

Self Cite

172

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Language learning is a three-way interaction between the input, the learner, and the interactional context (Bloom, 1974). This three-way interaction provides a general framework for understanding first and second language acquisition, in both naturalistic and formal contexts. In order to elaborate this general framework, we need to model its three components:1. The input. We need to know how the linguistic input can be structured to maximize effective learning. What aspects of the phonology, syntax, semantics, and morphology of the input does the learner use to "crack the code" of the new language? 2. The learner. We need to understand exactly how the cognitive abilities of the learner shape the process and outcome of second language instruction. 3. The context. Traditionally, the classroom environment maintains a rather uniform structure in which interaction is controlled by the instructor. How does this framework affect learning and how can it be varied to improve the learning process?This paper will examine these three components within the framework of the Competition Model (MacWhinney, 1987; MacWhinney & Bates, 1989). To quantify the role of the input in second language learning, the model relies on the concepts of cue reliability and availability. To characterize the cognitive abilities of the learner, the model relies on findings from cognitive neuroscience. To understand the role of the context, the model elaborates the concepts of environmental and social support. The Competition Model views both first and second language learning as constructive, data-driven processes that rely not on universals of linguistic structure, but on universals of cognitive structure. It attributes development to learning and transfer, rather than to the principles and parameters of Universal Grammar (Chomsky, 1965). The InputThe Competition Model is designed to quantify the ways in which distributional properties of the input control language learning and language processing. The basic claim of the model in regard to input is that language comprehension is based on the detection of a series of cues and the reliability and availability of these determines the strength of cues in comprehension. The model contrasts sharply with generative grammar in this regard. Generative grammar views language through the lens of abstract trees in a universal deep structure. The Competition Model recognizes the importance of surface phrase structure, but relates all sentence processing to cue detection and interpretation. Those cues that are highest in reliability and availability are the ones that most strongly control comprehension and which are acquired first during language learning.In order to elaborate this simple relation between cues and comprehension, we need to specify how languages distribute cues across sentences. To do this, the Competition Model has turned to crosslinguistic studies of sentence processing. In particular, the forms or

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Cue validity and sentence interpretation in English, German, and Italian

Abstract: Cue validity and sentence interpretation in English, German, and Italian U n i v e r s i t ä t P o t s d a mHumanwissenschaftliche Fakultät fi rst published in:

Cited by 393 publications

References 20 publications

Rational integration of noisy evidence and prior semantic expectations in sentence interpretation

Rational integration of noisy evidence and prior semantic expectations in sentence interpretation

One or More Labels on the Bottles? Notional Concord in Dutch and French

The competition model: the input, the context, and the brain

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