scholarly journals Experience-driven meaning affects lexical choices during language production

2021 ◽  
Author(s):  
Anne Vogt ◽  
Barbara Kaup ◽  
Rasha Abdel Rahman
Keyword(s):  
Language Processing ◽  
Language Production ◽  
Similarity Measures ◽  
Palm Tree ◽  
Lexical Selection ◽  
Spatial Cues ◽  
Hybrid Approaches ◽  
Verbal Messages ◽  
The Many ◽  
Spatial Locations

The role of meaning facets based on sensorimotor experiences is well-investigated in comprehension but has received little attention in language production research. In two experiments, we investigated whether experiential traces of space influenced lexical choices when participants completed visually-presented sentence fragments (e.g., ‘You are at the sea and you see a ...’) with spoken nouns (e.g., ‘dolphin’, ‘palm tree’). The words were presented consecutively in an ascending or descending direction, starting from the center of the screen. These physical spatial cues did not influence lexical choices. However, the produced nouns met the spatial characteristics of the broader sentence contexts such that the typical spatial locations of the produced noun referents were predicted by the location of the situations described by the sentence fragments (i. e., upper or lower sphere). By including distributional semantic similarity measures derived from computing cosine values between sentence nouns and produced nouns using a web-based text corpus, we show that the meaning dimension of ‘location in space’ guides lexical selection during speaking. We discuss the relation of this spatial meaning dimension to accounts of experientially grounded and usage-based theories of language processing and their combination in hybrid approaches. In doing so, we contribute to a more comprehensive understanding of the many facets of meaning processing during language production and their impact on the words we select to express verbal messages.

Using NLP for Fact Checking: A Survey

Designs ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 42
Author(s):  
Eric Lazarski ◽  
Mahmood Al-Khassaweneh ◽  
Cynthia Howard
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Computer Science ◽  
Language Processing ◽  
The Internet ◽  
Fake News ◽  
Fact Checking ◽  
The Many ◽  
Human Powered ◽  
The Web

In recent years, disinformation and “fake news” have been spreading throughout the internet at rates never seen before. This has created the need for fact-checking organizations, groups that seek out claims and comment on their veracity, to spawn worldwide to stem the tide of misinformation. However, even with the many human-powered fact-checking organizations that are currently in operation, disinformation continues to run rampant throughout the Web, and the existing organizations are unable to keep up. This paper discusses in detail recent advances in computer science to use natural language processing to automate fact checking. It follows the entire process of automated fact checking using natural language processing, from detecting claims to fact checking to outputting results. In summary, automated fact checking works well in some cases, though generalized fact checking still needs improvement prior to widespread use.

scholarly journals Evolution of Semantic Similarity—A Survey

2021 ◽  
Vol 54 (2) ◽  
pp. 1-37
Author(s):  
Dhivya Chandrasekaran ◽  
Vijay Mago
Keyword(s):  
Natural Language ◽  
Semantic Similarity ◽  
Language Processing ◽  
Hybrid Methods ◽  
Research Work ◽  
Similarity Measures ◽  
Text Data ◽  
Knowledge Based ◽  
Open Research ◽  
Research Problems

Estimating the semantic similarity between text data is one of the challenging and open research problems in the field of Natural Language Processing (NLP). The versatility of natural language makes it difficult to define rule-based methods for determining semantic similarity measures. To address this issue, various semantic similarity methods have been proposed over the years. This survey article traces the evolution of such methods beginning from traditional NLP techniques such as kernel-based methods to the most recent research work on transformer-based models, categorizing them based on their underlying principles as knowledge-based, corpus-based, deep neural network–based methods, and hybrid methods. Discussing the strengths and weaknesses of each method, this survey provides a comprehensive view of existing systems in place for new researchers to experiment and develop innovative ideas to address the issue of semantic similarity.

scholarly journals Towards Accurate and Efficient Chinese Part-of-Speech Tagging

2016 ◽  
Vol 42 (3) ◽  
pp. 391-419 ◽  
Author(s):  
Weiwei Sun ◽  
Xiaojun Wan
Keyword(s):  
Hybrid Systems ◽  
Language Processing ◽  
Large Scale ◽  
Unlabeled Data ◽  
Training Data ◽  
Test Time ◽  
System Combination ◽  
Pos Tagging ◽  
Hybrid Approaches ◽  
Lexical Relations

From the perspective of structural linguistics, we explore paradigmatic and syntagmatic lexical relations for Chinese POS tagging, an important and challenging task for Chinese language processing. Paradigmatic lexical relations are explicitly captured by word clustering on large-scale unlabeled data and are used to design new features to enhance a discriminative tagger. Syntagmatic lexical relations are implicitly captured by syntactic parsing in the constituency formalism, and are utilized via system combination. Experiments on the Penn Chinese Treebank demonstrate the importance of both paradigmatic and syntagmatic relations. Our linguistically motivated, hybrid approaches yield a relative error reduction of 18% in total over state-of-the-art baselines. Despite the effectiveness to boost accuracy, computationally expensive parsers make hybrid systems inappropriate for many realistic NLP applications. In this article, we are also concerned with improving tagging efficiency at test time. In particular, we explore unlabeled data to transfer the predictive power of hybrid models to simple sequence models. Specifically, hybrid systems are utilized to create large-scale pseudo training data for cheap models. Experimental results illustrate that the re-compiled models not only achieve high accuracy with respect to per token classification, but also serve as a front-end to a parser well.

Spoken language comprehension: insights from eye movements

2007 ◽  
pp. 308-326 ◽  
Author(s):  
Michael K. Tanenhaus
Keyword(s):  
Eye Movements ◽  
Language Processing ◽  
Language Comprehension ◽  
Language Production ◽  
World Literature ◽  
Spoken Language ◽  
Response Measure ◽  
Visual World ◽  
Spoken Language Processing ◽  
Spoken Language Comprehension

Recently, eye movements have become a widely used response measure for studying spoken language processing in both adults and children, in situations where participants comprehend and generate utterances about a circumscribed “Visual World” while fixation is monitored, typically using a free-view eye-tracker. Psycholinguists now use the Visual World eye-movement method to study both language production and language comprehension, in studies that run the gamut of current topics in language processing. Eye movements are a response measure of choice for addressing many classic questions about spoken language processing in psycholinguistics. This article reviews the burgeoning Visual World literature on language comprehension, highlighting some of the seminal studies and examining how the Visual World approach has contributed new insights to our understanding of spoken word recognition, parsing, reference resolution, and interactive conversation. It considers some of the methodological issues that come to the fore when psycholinguists use eye movements to examine spoken language comprehension.

Word form retrieval in language production

2007 ◽  
pp. 470-488 ◽  
Author(s):  
Antje S. Meyer ◽  
Eva Belke
Keyword(s):  
Language Production ◽  
Knowledge Building ◽  
Word Production ◽  
Word Form ◽  
Lexical Selection ◽  
Single Word ◽  
Phonological Representations ◽  
Phonological Knowledge ◽  
Phonetic Code ◽  
Selection Of

Current models of word form retrieval converge on central assumptions. They all distinguish between morphological, phonological, and phonetic representations and processes; they all assume morphological and phonological decomposition, and agree on the main processing units at these levels. In addition, all current models of word form postulate the same basic retrieval mechanisms: activation and selection of units. Models of word production often distinguish between processes concerning the selection of a single word unit from the mental lexicon and the retrieval of the associated word form. This article explores lexical selection and word form retrieval in language production. Following the distinctions in linguistic theory, it discusses morphological encoding, phonological encoding, and phonetic encoding. The article also considers the representation of phonological knowledge, building of phonological representations, segmental retrieval, retrieval of metrical information, generating the phonetic code of words, and a model of word form retrieval.

Brain-imaging studies of language production

2007 ◽  
pp. 546-564
Author(s):  
Peter Indefrey
Keyword(s):  
Brain Imaging ◽  
Language Production ◽  
Brain Regions ◽  
Code Word ◽  
Word Production ◽  
Production Model ◽  
Exact Nature ◽  
Lexical Selection ◽  
Imaging Studies ◽  
Independent Evidence

This article adopts the production model of Levelt to discuss brain imaging studies of continuous speech. Conclusions about the involvement of brain regions in processes of language production are mainly drawn on the basis of the presence or absence of processing components of speaking in certain experimental tasks. Such conclusions are largely theory independent, because differences between current models do not concern the assumed processing levels but the exact nature of the information flow between them. In a second step, the article tests some of these conclusions by comparing the few available data on activation time courses of brain regions and independent evidence on the timing of processes in language production. It also discusses brain regions involved in word production, conceptually driven lexical selection, phonological code (word form) retrieval, phonological encoding, phonetic encoding and articulation, self-monitoring, whether the hemodynamic core areas are necessary for word production, and bilingual language production.

Division and Classification

2019 ◽  
pp. 34-54
Author(s):  
Paolo Crivelli
Keyword(s):  
Spatial Location ◽  
One And Many ◽  
The Many ◽  
The One ◽  
Spatial Locations ◽  
Different Parts

The Philebus presents some arguments for the paradoxical claim that the many are one and the one many. The most serious of these arguments concerns the multiple spatial locations of an attribute. For instance, since the attribute man belongs to many men, it is in them, and it is therefore both one and many (for it is in them either by having different parts of itself contained in them or by being wholly contained in each of them). Plato maintains that this argument goes astray. He appeals to division and collection, the procedures linked with definition and classification. He probably has in mind a mereological model of particulars, whereby perceptible particulars are mixtures whose ingredients are the attributes which they partake of. Among the ingredients of a perceptible particular there are properties that specify its spatial location, so the problem of the multiple spatial location of an attribute evaporates.

Language processing and language acquisition through the lens of Relational Morphology

2019 ◽  
pp. 201-232
Author(s):  
Ray Jackendoff ◽  
Jenny Audring
Keyword(s):  
Language Acquisition ◽  
Language Processing ◽  
Language Production ◽  
Long Term Memory ◽  
Spreading Activation ◽  
Linguistic Representations ◽  
Memory Network ◽  
Complex Words

This chapter asks what is happening to linguistic representations during language use, and how representations are formed in the course of language acquisition. It is shown how Relational Morphology’s theory of representations can be directly embedded into models of processing and acquisition. Central is that the lexicon, complete with schemas and relational links, constitutes the long-term memory network that supports language production and comprehension. The chapter first discusses processing: the nature of working memory; promiscuous (opportunistic) processing; spreading activation; priming; probabilistic parsing; the balance between storage and computation in recognizing morphologically complex words; and the role of relational links and schemas in word retrieval. It then turns to acquisition, which is to be thought of as adding nodes and relational links to the lexical network. The general approach is based on the Propose but Verify procedure of Trueswell et al. (2013), plus conservative generalization, as in usage-based approaches.

scholarly journals Neural systems for sign language production: Mechanisms supporting lexical selection, phonological encoding, and articulation

2004 ◽  
Vol 23 (3) ◽  
pp. 156-167 ◽  
Author(s):  
Lucila San José-Robertson ◽  
David P. Corina ◽  
Debra Ackerman ◽  
Andre Guillemin ◽  
Allen R. Braun
Keyword(s):  
Sign Language ◽  
Language Production ◽  
Neural Systems ◽  
Phonological Encoding ◽  
Lexical Selection ◽  
Production Mechanisms

Speech and Language Production at Age 2

1991 ◽  
Vol 34 (4) ◽  
pp. 879-892 ◽  
Author(s):  
Lauren K. Nelson ◽  
Harold R. Bauer
Keyword(s):  
Language Acquisition ◽  
Language Processing ◽  
Language Production ◽  
Complexity Analysis ◽  
Spontaneous Speech ◽  
Limited Capacity ◽  
Speech And Language ◽  
Lexical Items ◽  
Propositional Complexity ◽  
The Relationship

The purpose of this study was to explore how 2-year-old children manage the relationship between phonetic production and production of word combinations in their spontaneous speech. The subjects were 5 normally developing 2-year-olds who were participants in an ongoing longitudinal study of speech and language acquisition. Three measures were used to estimate phonetic production skills in the children’s spontaneous speech samples. These included a measure of the accuracy of consonant production (Percentage of Consonants Correct), and two estimators of phonetic complexity (phonetic products for utterance and word length units). Regression analyses were used to determine the relationship between complexity of word combinations, as measured by length of utterance in morphemes and a propositional complexity analysis, and utilization of phonetic production skills. The results revealed modest tradeoffs between complexity of word combinations and accuracy of consonant production for 2 of the 5 children. The results also showed tradeoffs between complexity of word combinations and phonetic complexity of individual lexical items (phonetic product for words) for 4 of the 5 children. As the complexity of these 4 children’s multiword combinations increased, the phonetic complexity of individual lexical items decreased. These results are consistent with synergistic theories of language acquisition and language processing that emphasize dynamic tradeoffs in interactions among language processing levels in a limited capacity production system.

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