The Social Meaning of Contextualized Sibilant Alternations in Berlin German

In Berlin, the pronunciation of /ç/ as [ɕ] is associated with the multi-ethnic youth variety (Kiezdeutsch). This alternation is also known to be produced by French learners of German. While listeners form socio-cultural interpretations upon hearing language input, the associations differ depending on the listeners’ biases and stereotypes toward speakers or groups. Here, the contrast of interest concerns two speaker groups using the [ç]–[ɕ] alternation: multi-ethnic adolescents from Berlin neighborhoods carrying low social prestige in mainstream German society and French learners of German supposedly having higher cultural prestige. To understand the strength of associations between phonetic alternations and social attributes, we ran an Implicit Association Task with 131 participants (three groups varying in age and ethnic background (mono- vs. multi-ethnic German) using auditory and written stimuli. In experiment 1, participants categorized written words as having a positive (good) or negative (bad) valence and auditory stimuli containing pronunciation variations of /ç/ as canonical [ç] (labeled Hochdeutsch [a term used in Germany for Standard German]) or non-canonical [ɕ] (labeled Kiezdeutsch). In experiment 2, identical auditory stimuli were used but the label Kiezdeutsch was changed to French Accent. Results show faster reaction times when negative categories and non-canonical pronunciations or positive categories and canonical pronunciations were mapped to the same response key, indicating a tight association between value judgments and concept categories. Older German listeners (OMO) match a supposed Kiezdeutsch accent more readily with negatively connotated words compared to a supposed French accent, while younger German listeners (YMO) seem to be indifferent toward this variation. Young multi-ethnic listeners (YMU), however, seem to associate negative concepts more strongly with a supposed French accent compared to Kiezdeutsch. These results demonstrate how social and cultural contextualization influences language interpretation and evaluation. We interpret our findings as a loss of cultural prestige of French speakers for the YMO group compared to the OMO group: younger urban listeners do not react differently to these contextual primes. YMU listeners, however, show a positive bias toward their in-group. Our results point to implicit listener attitudes, beliefs, stereotypes and shared world knowledge as significant factors in culturally- and socially situated language processing.

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A WORD-BASED CHINESE LANGUAGE UNDERSTANDING SYSTEM

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001488000042 ◽

1988 ◽

Vol 02 (01) ◽

pp. 25-35

Author(s):

TIAN-SHUN YAO

Keyword(s):

Natural Language Processing ◽

Natural Language ◽

Language Processing ◽

Chinese Language ◽

Computer Programs ◽

World Knowledge ◽

Knowledge Source ◽

Language Understanding ◽

Language Analysis ◽

The World

With the word-based theory of natural language processing, a word-based Chinese language understanding system has been developed. In the light of psychological language analysis and the features of the Chinese language, this theory of natural language processing is presented with the description of the computer programs based on it. The heart of the system is to define a Total Information Dictionary and the World Knowledge Source used in the system. The purpose of this research is to develop a system which can understand not only Chinese sentences but also the whole text.

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Some Factors Affecting Reaction Times to Auditory Stimuli in Mental Patients

Journal of Mental Science ◽

10.1192/bjp.100.419.462 ◽

1954 ◽

Vol 100 (419) ◽

pp. 462-477 ◽

Cited By ~ 15

Author(s):

K. R. L. Hall ◽

E. Stride

Keyword(s):

Reaction Time ◽

Visual Perception ◽

Visual Stimuli ◽

Reaction Times ◽

Auditory Stimuli ◽

Factors Affecting ◽

Mental Patients ◽

Personal Equation ◽

Work Up

A number of studies on reaction time (R.T.) latency to visual and auditory stimuli in psychotic patients has been reported since the first investigations on the personal equation were carried out. The general trends from the work up to 1943 are well summarized by Hunt (1944), while Granger's (1953) review of “Personality and visual perception” contains a summary of the studies on R.T. to visual stimuli.

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Anaphora resolution without world knowledge

DELTA Documentação de Estudos em Lingüística Teórica e Aplicada ◽

10.1590/s0102-44502003000100007 ◽

2003 ◽

Vol 19 (1) ◽

pp. 181-200 ◽

Cited By ~ 1

Author(s):

Vilson J. Leffa

Keyword(s):

Language Processing ◽

Expository Text ◽

Internal Representation ◽

Schema Theory ◽

Anaphora Resolution ◽

Semantic Features ◽

World Knowledge ◽

Semantic Constraints ◽

Pronominal Anaphora ◽

Sentence Subject

A typical problem in the resolution of pronominal anaphora is the presence of more than one candidate for the antecedent of the pronoun. Considering two English sentences like (1) "People buy expensive cars because they offer more status" and (2) "People buy expensive cars because they want more status" we can see that the two NPs "people" and "expensive cars", from a purely syntactic perspective, are both legitimate candidates as antecedents for the pronoun "they". This problem has been traditionally solved by using world knowledge (e.g. schema theory), where, through an internal representation of the world, we "know" that cars "offer" status and people "want" status. The assumption in this paper is that the use of world knowledge does not explain how the disambiguation process works and alternative explanations should be explored. Using a knowledge poor approach (explicit information from the text rather than implicit world knowledge) the study investigates to what extent syntactic and semantic constraints can be used to resolve anaphora. For this purpose, 1,400 examples of the word "they" were randomly selected from a corpus of 10,000,000 words of expository text in English. Antecedent candidates for each case were then analyzed and classified in terms of their syntactic functions in the sentence (subject, object, etc.) and semantic features (+ human, + animate, etc.). It was found that syntactic constraints resolved 85% of the cases. When combined with semantic constraints the resolution rate rose to 98%. The implications of the findings for Natural Language Processing are discussed.

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Conditionals on crutches: Expanding the modal horizon

10.31234/osf.io/tqg2e ◽

2020 ◽

Author(s):

Dario Paape ◽

Malte Zimmermann

Keyword(s):

Computational Modeling ◽

Reaction Times ◽

Process Models ◽

Cognitive Mechanisms ◽

Value Judgments ◽

Value Judgment ◽

Counterfactual Conditionals ◽

Modeling Techniques ◽

On Line ◽

Truth Value

Using truth-value judgment tasks, we investigated the on-line processing of counterfactual conditionals such as "If kangaroos had no tails, they would topple over". Face-value plausibility of the counterfactual as well as the complexity of the antecedent were manipulated. Results show that readers' judgments deviate from face-value plausibility more often when the antecedent is complex, and when the counterfactual is plausible rather than implausible. We interpret our results based on the modal horizon assumption of von Fintel (2001) and argue that they are compatible with a variably strict semantics for counterfactuals (Lewis, 1973). We make use of computational modeling techniques to account for reaction times and truth-value judgments simultaneously, showing that implementing detailed process models deepens our understanding of the cognitive mechanisms triggered by linguistic stimuli.

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Comparative analysis of reactions to visual and auditory stimuli in research on EEG evoked potentials

Journal of Computer Sciences Institute ◽

10.35784/jcsi.673 ◽

2018 ◽

Vol 7 ◽

pp. 172-177

Author(s):

Łukasz Tyburcy ◽

Małgorzata Plechawska-Wójcik

Keyword(s):

Comparative Analysis ◽

Evoked Potentials ◽

Auditory Stimulus ◽

Visual Stimulus ◽

Visual Stimuli ◽

Reaction Times ◽

Auditory Stimuli

The paper describes results of comparison of reactions times to visual and auditory stimuli using EEG evoked potentials. Two experiments were used to applied. The first one explored reaction times to visual stimulus and the second one to auditory stimulus. After conducting an analysis of data, received results enable determining that visual stimuli evoke faster reactions than auditory stimuli.

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Constructing the Mandarin Phonological Network: Novel Syllable Inventory Used to Identify Schematic Segmentation

Complexity ◽

10.1155/2019/6979830 ◽

2019 ◽

Vol 2019 ◽

pp. 1-21 ◽

Cited By ~ 5

Author(s):

Karl D. Neergaard ◽

Chu-Ren Huang

Keyword(s):

Language Processing ◽

Phonological Processing ◽

Network Science ◽

Reaction Times ◽

Mental Lexicon ◽

Selection Procedure ◽

Clustering Coefficient ◽

The Novel ◽

Lexical Tone ◽

Syllable Segmentation

The purpose of this study was to construct, measure, and identify a schematic representation of phonological processing in the tonal language Mandarin Chinese through the combination of network science and psycholinguistic tasks. Two phonological association tasks were performed with native Mandarin speakers to identify an optimal phonological annotation system. The first task served to compare two existing syllable inventories and to construct a novel system where either performed poorly. The second task validated the novel syllable inventory. In both tasks, participants were found to manipulate lexical items at each possible syllable location, but preferring to maintain whole syllables while manipulating lexical tone in their search through the mental lexicon. The optimal syllable inventory was then used as the basis of a Mandarin phonological network. Phonological edit distance was used to construct sixteen versions of the same network, which we titled phonological segmentation neighborhoods (PSNs). The sixteen PSNs were representative of every proposal to date of syllable segmentation. Syllable segmentation and whether or not lexical tone was treated as a unit both affected the PSNs’ topologies. Finally, reaction times from the second task were analyzed through a model selection procedure with the goal of identifying which of the sixteen PSNs best accounted for the mental target during the task. The identification of the tonal complex-vowel segmented PSN (C_V_C_T) was indicative of the stimuli characteristics and the choices participants made while searching through the mental lexicon. The analysis revealed that participants were inhibited by greater clustering coefficient (interconnectedness of words according to phonological similarity) and facilitated by lexical frequency. This study illustrates how network science methods add to those of psycholinguistics to give insight into language processing that was not previously attainable.

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A Constraint-Based Hypergraph Partitioning Approach to Coreference Resolution

Computational Linguistics ◽

10.1162/coli_a_00151 ◽

2013 ◽

Vol 39 (4) ◽

pp. 847-884 ◽

Cited By ~ 7

Author(s):

Emili Sapena ◽

Lluís Padró ◽

Jordi Turmo

Keyword(s):

Language Processing ◽

State Of The Art ◽

The State ◽

Classification Model ◽

Coreference Resolution ◽

World Knowledge ◽

Relaxation Labeling ◽

Hypergraph Partitioning ◽

Lack Of Information ◽

New Information

This work is focused on research in machine learning for coreference resolution. Coreference resolution is a natural language processing task that consists of determining the expressions in a discourse that refer to the same entity. The main contributions of this article are (i) a new approach to coreference resolution based on constraint satisfaction, using a hypergraph to represent the problem and solving it by relaxation labeling; and (ii) research towards improving coreference resolution performance using world knowledge extracted from Wikipedia. The developed approach is able to use an entity-mention classification model with more expressiveness than the pair-based ones, and overcome the weaknesses of previous approaches in the state of the art such as linking contradictions, classifications without context, and lack of information evaluating pairs. Furthermore, the approach allows the incorporation of new information by adding constraints, and research has been done in order to use world knowledge to improve performances. RelaxCor, the implementation of the approach, achieved results at the state-of-the-art level, and participated in international competitions: SemEval-2010 and CoNLL-2011. RelaxCor achieved second place in CoNLL-2011.

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Design and realization of a modular architecture for textual entailment

Natural Language Engineering ◽

10.1017/s1351324913000351 ◽

2013 ◽

Vol 21 (2) ◽

pp. 167-200 ◽

Cited By ~ 10

Author(s):

SEBASTIAN PADÓ ◽

TAE-GIL NOH ◽

ASHER STERN ◽

RUI WANG ◽

ROBERTO ZANOLI

Keyword(s):

Natural Language ◽

Language Processing ◽

Linguistic Analysis ◽

Knowledge Bases ◽

Practical Implementation ◽

World Knowledge ◽

Modular Architecture ◽

Open Platform ◽

The Core ◽

Textual Entailment

AbstractA key challenge at the core of many Natural Language Processing (NLP) tasks is the ability to determine which conclusions can be inferred from a given natural language text. This problem, called theRecognition of Textual Entailment (RTE), has initiated the development of a range of algorithms, methods, and technologies. Unfortunately, research on Textual Entailment (TE), like semantics research more generally, is fragmented into studies focussing on various aspects of semantics such as world knowledge, lexical and syntactic relations, or more specialized kinds of inference. This fragmentation has problematic practical consequences. Notably, interoperability among the existing RTE systems is poor, and reuse of resources and algorithms is mostly infeasible. This also makes systematic evaluations very difficult to carry out. Finally, textual entailment presents a wide array of approaches to potential end users with little guidance on which to pick. Our contribution to this situation is the novel EXCITEMENT architecture, which was developed to enable and encourage the consolidation of methods and resources in the textual entailment area. It decomposes RTE into components with strongly typed interfaces. We specify (a) a modular linguistic analysis pipeline and (b) a decomposition of the ‘core’ RTE methods into top-level algorithms and subcomponents. We identify four major subcomponent types, including knowledge bases and alignment methods. The architecture was developed with a focus on generality, supporting all major approaches to RTE and encouraging language independence. We illustrate the feasibility of the architecture by constructing mappings of major existing systems onto the architecture. The practical implementation of this architecture forms the EXCITEMENT open platform. It is a suite of textual entailment algorithms and components which contains the three systems named above, including linguistic-analysis pipelines for three languages (English, German, and Italian), and comprises a number of linguistic resources. By addressing the problems outlined above, the platform provides a comprehensive and flexible basis for research and experimentation in textual entailment and is available as open source software under the GNU General Public License.

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Neurobehavioral Correlates of Surprisal in Language Comprehension: A Neurocomputational Model

Frontiers in Psychology ◽

10.3389/fpsyg.2021.615538 ◽

2021 ◽

Vol 12 ◽

Author(s):

Harm Brouwer ◽

Francesca Delogu ◽

Noortje J. Venhuizen ◽

Matthew W. Crocker

Keyword(s):

Experimental Design ◽

Language Processing ◽

Language Comprehension ◽

Word Processing ◽

World Knowledge ◽

Behavioral Correlates ◽

Close Link ◽

Model Predictions ◽

Open Question ◽

Processing Difficulty

Expectation-based theories of language comprehension, in particular Surprisal Theory, go a long way in accounting for the behavioral correlates of word-by-word processing difficulty, such as reading times. An open question, however, is in which component(s) of the Event-Related brain Potential (ERP) signal Surprisal is reflected, and how these electrophysiological correlates relate to behavioral processing indices. Here, we address this question by instantiating an explicit neurocomputational model of incremental, word-by-word language comprehension that produces estimates of the N400 and the P600—the two most salient ERP components for language processing—as well as estimates of “comprehension-centric” Surprisal for each word in a sentence. We derive model predictions for a recent experimental design that directly investigates “world-knowledge”-induced Surprisal. By relating these predictions to both empirical electrophysiological and behavioral results, we establish a close link between Surprisal, as indexed by reading times, and the P600 component of the ERP signal. The resultant model thus offers an integrated neurobehavioral account of processing difficulty in language comprehension.

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Foreword

International Journal of Computers Communications & Control ◽

10.15837/ijccc.2011.3.2123 ◽

2011 ◽

Vol 6 (3) ◽

pp. 385 ◽

Cited By ~ 1

Author(s):

L.A. Zadeh

Keyword(s):

Fuzzy Logic ◽

Natural Language ◽

Language Processing ◽

Extension Principle ◽

Computing With Words ◽

World Knowledge ◽

Special Issue ◽

Large Measure ◽

Natural Languages ◽

Computer Scientists

I feel honored by the dedication of the Special Issue of IJCCC to me. I should like to express my deep appreciation to the distinguished Co-Editors and my good friends, Professors Balas, Dzitac and Teodorescu, and to distinguished contributors, for honoring me. The subjects which are addressed in the Special Issue are on the frontiers of fuzzy logic. The Foreword gives me an opportunity to share with the readers of the Journal my recent thoughts regarding a subject which I have been pondering about for many years - fuzzy logic and natural languages. The first step toward linking fuzzy logic and natural languages was my 1973 paper," Outline of a New Approach to the Analysis of Complex Systems and Decision Processes." Two key concepts were introduced in that paper. First, the concept of a linguistic variable - a variable which takes words as values; and second, the concept of a fuzzy if- then rule - a rule in which the antecedent and consequent involve linguistic variables. Today, close to forty years later, these concepts are widely used in most applications of fuzzy logic. The second step was my 1978 paper, "PRUF - a Meaning Representation Language for Natural Languages." This paper laid the foundation for a series of papers in the eighties in which a fairly complete theory of fuzzy - logic-based semantics of natural languages was developed. My theory did not attract many followers either within the fuzzy logic community or within the linguistics and philosophy of languages communities. There is a reason. The fuzzy logic community is largely a community of engineers, computer scientists and mathematicians - a community which has always shied away from semantics of natural languages. Symmetrically, the linguistics and philosophy of languages communities have shied away from fuzzy logic. In the early nineties, a thought that began to crystallize in my mind was that in most of the applications of fuzzy logic linguistic concepts play an important, if not very visible role. It is this thought that motivated the concept of Computing with Words (CW or CWW), introduced in my 1996 paper "Fuzzy Logic = Computing with Words." In essence, Computing with Words is a system of computation in which the objects of computation are words, phrases and propositions drawn from a natural language. The same can be said about Natural Language Processing (NLP.) In fact, CW and NLP have little in common and have altogether different agendas. In large measure, CW is concerned with solution of computational problems which are stated in a natural language. Simple example. Given: Probably John is tall. What is the probability that John is short? What is the probability that John is very short? What is the probability that John is not very tall? A less simple example. Given: Usually Robert leaves office at about 5 pm. Typically it takes Robert about an hour to get home from work. What is the probability that Robert is home at 6:l5 pm.? What should be noted is that CW is the only system of computation which has the capability to deal with problems of this kind. The problem-solving capability of CW rests on two key ideas. First, employment of so-called restriction-based semantics (RS) for translation of a natural language into a mathematical language in which the concept of a restriction plays a pivotal role; and second, employment of a calculus of restrictions - a calculus which is centered on the Extension Principle of fuzzy logic. What is thought-provoking is that neither traditional mathematics nor standard probability theory has the capability to deal with computational problems which are stated in a natural language. Not having this capability, it is traditional to dismiss such problems as ill-posed. In this perspective, perhaps the most remarkable contribution of CW is that it opens the door to empowering of mathematics with a fascinating capability - the capability to construct mathematical solutions of computational problems which are stated in a natural language. The basic importance of this capability derives from the fact that much of human knowledge, and especially world knowledge, is described in natural language. In conclusion, only recently did I begin to realize that the formalism of CW suggests a new and challenging direction in mathematics - mathematical solution of computational problems which are stated in a natural language. For mathematics, this is an unexplored territory.

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