Good intentions and bad words

2001 ◽  
Vol 24 (6) ◽  
pp. 1110-1111 ◽  
Author(s):  
Frank C. Keil
Keyword(s):  
Language Acquisition ◽  
Word Learning ◽  
Word Meaning ◽  
Learning System ◽  
Acquisition System ◽  
Critical Questions ◽  
Strong Case

Bloom makes a strong case that word meaning acquisition does not require a dedicated word learning system. This conclusion, however, does not argue against a dedicated language acquisition system for syntax, morphology, and aspects of semantics. Critical questions are raised as to why word meaning should be so different from other aspects of language in the course of acquisition.

scholarly journals Prosody and Function Words Cue the Acquisition of Word Meanings in 18-Month-Old Infants

2019 ◽  
Vol 30 (3) ◽  
pp. 319-332 ◽  
Author(s):  
Alex de Carvalho ◽  
Angela Xiaoxue He ◽  
Jeffrey Lidz ◽  
Anne Christophe
Keyword(s):  
Language Acquisition ◽  
Word Learning ◽  
Syntactic Structure ◽  
Word Meaning ◽  
Lexical Acquisition ◽  
Function Words ◽  
Word Meanings ◽  
Syntactic Information ◽  
And Function ◽  
Speech Melody

Language acquisition presents a formidable task for infants, for whom word learning is a crucial yet challenging step. Syntax (the rules for combining words into sentences) has been robustly shown to be a cue to word meaning. But how can infants access syntactic information when they are still acquiring the meanings of words? We investigated the contribution of two cues that may help infants break into the syntax and give a boost to their lexical acquisition: phrasal prosody (speech melody) and function words, both of which are accessible early in life and correlate with syntactic structure in the world’s languages. We show that 18-month-old infants use prosody and function words to recover sentences’ syntactic structure, which in turn constrains the possible meanings of novel words: Participants ( N = 48 in each of two experiments) interpreted a novel word as referring to either an object or an action, given its position within the prosodic-syntactic structure of sentences.

scholarly journals Psycholinguistic techniques and resources in second language acquisition research

2012 ◽  
Vol 28 (1) ◽  
pp. 113-127 ◽  
Author(s):  
Leah Roberts
Keyword(s):  
Second Language ◽  
Second Language Acquisition ◽  
Language Acquisition ◽  
Real Time ◽  
Current Knowledge ◽  
Research Topics ◽  
Critical Questions ◽  
Online Processing ◽  
Practical Information

In this article, a survey of current psycholinguistic techniques relevant to second language acquisition (SLA) research is presented. I summarize many of the available methods and discuss their use with particular reference to two critical questions in current SLA research: (1) What does a learner’s current knowledge of the second language (L2) look like?; (2) How do learners process the L2 in real time? The aim is to show how psycholinguistic techniques that capture real-time (online) processing can elucidate such questions; to suggest methods best suited to particular research topics, and types of participants; and to offer practical information on the setting up of a psycholinguistics laboratory.

Morphological Knowledge as an Aid to Word Learning: A Cross-Situational Word Learning Study

2021 ◽  
Author(s):  
Sara Finley
Keyword(s):  
Word Learning ◽  
Word Meaning ◽  
Learning Task ◽  
Artificial Language ◽  
Initial Training ◽  
Experimental Conditions ◽  
Morphological Knowledge ◽  
Semantic Categories ◽  
English Speaking ◽  
Morphological Cues

The present study explores morphological bootstrapping in cross-situational word learning. Adult, English-speaking participants were exposed to novel words from an artificial language from three different semantic categories: fruit, animals, and vehicles. In the Experimental conditions, the final CV syllable was consistent across categories (e.g., /-ke/ for fruits), while in the Control condition, the endings were the same, but were assigned to words randomly. After initial training on the morphology under various degrees of referential uncertainty, participants were given a cross-situational word learning task with high referential uncertainty. With poor statistical cues to learn the words across trials, participants were forced to rely on the morphological cues to word meaning. In Experiments 1-3, participants in the Experimental conditions repeatedly outperformed participants in the Control conditions. In Experiment 4, when referential uncertainty was high in both parts of the experiment, there was no evidence of learning or making use of the morphological cues. These results suggest that learners apply morphological cues to word meaning only once they are reliably available.

Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning

2009 ◽  
Vol 20 (5) ◽  
pp. 578-585 ◽  
Author(s):  
Michael C. Frank ◽  
Noah D. Goodman ◽  
Joshua B. Tenenbaum
Keyword(s):  
Computational Model ◽  
Word Learning ◽  
Word Meaning ◽  
Mutual Exclusivity ◽  
Object Individuation ◽  
Word Meanings ◽  
Inference Problems ◽  
Corpus Data ◽  
Situational Learning

Word learning is a “chicken and egg” problem. If a child could understand speakers' utterances, it would be easy to learn the meanings of individual words, and once a child knows what many words mean, it is easy to infer speakers' intended meanings. To the beginning learner, however, both individual word meanings and speakers' intentions are unknown. We describe a computational model of word learning that solves these two inference problems in parallel, rather than relying exclusively on either the inferred meanings of utterances or cross-situational word-meaning associations. We tested our model using annotated corpus data and found that it inferred pairings between words and object concepts with higher precision than comparison models. Moreover, as the result of making probabilistic inferences about speakers' intentions, our model explains a variety of behavioral phenomena described in the word-learning literature. These phenomena include mutual exclusivity, one-trial learning, cross-situational learning, the role of words in object individuation, and the use of inferred intentions to disambiguate reference.

An exploratory study of linguistic–colour associations across languages in multilingual synaesthetes

2009 ◽  
Vol 62 (7) ◽  
pp. 1343-1355 ◽  
Author(s):  
Kylie J. Barnett ◽  
Joanne Feeney ◽  
Michael Gormley ◽  
Fiona N. Newell
Keyword(s):  
Language Acquisition ◽  
Exploratory Study ◽  
Critical Period ◽  
Semantic Information ◽  
Word Meaning ◽  
Age Of Acquisition ◽  
Visual Structure ◽  
Visual Properties

In one of the most common forms of synaesthesia, linguistic–colour synaesthesia, colour is induced by stimuli such as numbers, letters, days of the week, and months of the year. It is not clear, however, whether linguistic–colour synaesthesia is determined more by higher level semantic information—that is, word meaning—or by lower level grapheme or phoneme structure. To explore this issue, we tested whether colour is consistently induced by grapheme or phoneme form or word meaning in bilingual and trilingual linguistic–colour synaesthetes. We reasoned that if the induced colour was related to word meaning, rather than to the acoustic or visual properties of the words, then the induced colours would remain consistent across languages. We found that colours were not consistently related to word meaning across languages. Instead, induced colours were more related to form properties of the word across languages, particularly visual structure. However, the type of inducing stimulus influenced specific colour associations. For example, colours to months of the year were more consistent across languages than were colours to numbers or days of the week. Furthermore, the effect of inducing stimuli was also associated with the age of acquisition of additional languages. Our findings are discussed with reference to a critical period in language acquisition on synaesthesia.

Towards an Automated Language Acquisition System for Grounded Agency

2021 ◽  
pp. 23-43
Author(s):  
James R. Kubricht ◽  
Sharon Small ◽  
Ting Liu ◽  
Peter H. Tu
Keyword(s):  
Language Acquisition ◽  
Acquisition System

scholarly journals The Impossibility of Language Acquisition (and How They Do It)

2019 ◽  
Vol 5 (1) ◽  
pp. 1-24 ◽  
Author(s):  
Lila R. Gleitman ◽  
Mark Y. Liberman ◽  
Cynthia A. McLemore ◽  
Barbara H. Partee
Keyword(s):  
Language Acquisition ◽  
Cognitive Science ◽  
Argument Structure ◽  
Word Meaning ◽  
Research Community ◽  
Psychological Perspective ◽  
Syntactic Bootstrapping ◽  
Language Input ◽  
Answering Questions

This autobiographical article, which began as an interview, reports some reflections by Lila Gleitman on the development of her thinking and her research—in concert with a host of esteemed collaborators over the years—on issues of language and mind, focusing on how language is acquired. Gleitman entered the field of linguistics as a student of Zellig Harris, and learned firsthand of Noam Chomsky's early work. She chose the psychological perspective, later helping to found the field of cognitive science; and with her husband and long-term collaborator, Henry Gleitman, for over 50 years fostered a continuing research community aimed at answering questions such as: When language input to the child is restricted, what is left to explain language acquisition? The studies reported here find that argument structure encoded in the syntax is key (syntactic bootstrapping) and that children learn word meaning in epiphanies (propose but verify).

How many words can my robot learn?

2007 ◽  
Vol 8 (1) ◽  
pp. 53-81 ◽  
Author(s):  
Luís Seabra Lopes ◽  
Aneesh Chauhan
Keyword(s):  
Word Learning ◽  
Real World ◽  
Scale Up ◽  
Human Robot Interaction ◽  
Learning System ◽  
Evaluation Methodology ◽  
Robot Interaction ◽  
Instructor Feedback ◽  
Discriminatory Capacity ◽  
Robotic Agent

This paper addresses word learning for human–robot interaction. The focus is on making a robotic agent aware of its surroundings, by having it learn the names of the objects it can find. The human user, acting as instructor, can help the robotic agent ground the words used to refer to those objects. A lifelong learning system, based on one-class learning, was developed (OCLL). This system is incremental and evolves with the presentation of any new word, which acts as a class to the robot, relying on instructor feedback. A novel experimental evaluation methodology, that takes into account the open-ended nature of word learning, is proposed and applied. This methodology is based on the realization that a robot’s vocabulary will be limited by its discriminatory capacity which, in turn, depends on its sensors and perceptual capabilities. The results indicate that the robot’s representations are capable of incrementally evolving by correcting class descriptions, based on instructor feedback to classification results. In successive experiments, it was possible for the robot to learn between 6 and 12 names of real-world office objects. Although these results are comparable to those obtained by other authors, there is a need to scale-up. The limitations of the method are discussed and potential directions for improvement are pointed out.

Sign in / Sign up

Export Citation Format

Share Document