Emotion and language: valence and arousal affect word recognition

Emotion influences most aspects of cognition and behavior, but emotional factors are conspicuously absent from current models of word recognition. The influence of emotion on word recognition has mostly been reported in prior studies on the automatic vigilance for negative stimuli, but the precise nature of this relationship is unclear. Various models of automatic vigilance have claimed that the effect of valence on response times is categorical, an inverted U, or interactive with arousal. In the present study, we used a sample of 12,658 words and included many lexical and semantic control factors to determine the precise nature of the effects of arousal and valence on word recognition. Converging empirical patterns observed in word-level and trial-level data from lexical decision and naming indicate that valence and arousal exert independent monotonic effects: Negative words are recognized more slowly than positive words, and arousing words are recognized more slowly than calming words. Valence explained about 2% of the variance in word recognition latencies, whereas the effect of arousal was smaller. Valence and arousal do not interact, but both interact with word frequency, such that valence and arousal exert larger effects among low-frequency words than among high-frequency words. These results necessitate a new model of affective word processing whereby the degree of negativity monotonically and independently predicts the speed of responding. This research also demonstrates that incorporating emotional factors, especially valence, improves the performance of models of word recognition

Acquiring Word-Meaning Mappings for Natural Language Interfaces

This paper focuses on a system, WOLFIE (WOrd Learning From Interpreted Examples), that acquires a semantic lexicon from a corpus of sentences paired with semantic representations. The lexicon learned consists of phrases paired with meaning representations. WOLFIE is part of an integrated system that learns to transform sentences into representations such as logical database queries. Experimental results are presented demonstrating WOLFIE's ability to learn useful lexicons for a database interface in four different natural languages. The usefulness of the lexicons learned by WOLFIE are compared to those acquired by a similar system, with results favorable to WOLFIE. A second set of experiments demonstrates WOLFIE's ability to scale to larger and more difficult, albeit artificially generated, corpora. In natural language acquisition, it is difficult to gather the annotated data needed for supervised learning; however, unannotated data is fairly plentiful. Active learning methods attempt to select for annotation and training only the most informative examples, and therefore are potentially very useful in natural language applications. However, most results to date for active learning have only considered standard classification tasks. To reduce annotation effort while maintaining accuracy, we apply active learning to semantic lexicons. We show that active learning can significantly reduce the number of annotated examples required to achieve a given level of performance

Decline and fall:a biological, developmental, and psycholinguistic account of deliberative language processes and ageing

Background: This paper reviews the role of deliberative processes in language: those language processes that require central resources, in contrast to the automatic processes of lexicalisation, word retrieval, and parsing. 10 Aims: We describe types of deliberative processing, and show how these processes underpin high-level processes that feature strongly in language. We focus on metalin- guistic processing, strategic processing, inhibition, and planning. We relate them to frontal-lobe function and the development of the fronto-striate loop. We then focus on the role of deliberative processes in normal and pathological development and ageing, 15 and show how these processes are particularly susceptible to deterioration with age. In particular, many of the commonly observed language impairments encountered in ageing result from a decline in deliberative processing skills rather than in automatic language processes. Main Contribution: We argue that central processing plays a larger and more important 20 role in language processing and acquisition than is often credited. Conclusions: Deliberative language processes permeate language use across the lifespan. They are particularly prone to age-related loss. We conclude by discussing implications for therapy

Requirements for Information Extraction for Knowledge Management

Knowledge Management (KM) systems inherently suffer from the knowledge acquisition bottleneck - the difficulty of modeling and formalizing knowledge relevant for specific domains. A potential solution to this problem is Information Extraction (IE) technology. However, IE was originally developed for database population and there is a mismatch between what is required to successfully perform KM and what current IE technology provides. In this paper we begin to address this issue by outlining requirements for IE based KM

On the Automaticity and Ethics of Belief

Recently, philosophers have appealed to empirical studies to argue that whenever we think that p, we automatically believe that p (Millikan 2004; Mandelbaum 2014; Levy and Mandelbaum 2014). Levy and Mandelbaum (2014) have gone further and claimed that the automaticity of believing has implications for the ethics of belief in that it creates epistemic obligations for those who know about their automatic belief acquisition. I use theoretical considerations and psychological findings to raise doubts about the empirical case for the view that we automatically believe what we think. Furthermore, I contend that even if we set these doubts aside, Levy and Mandelbaum’s argument to the effect that the automaticity of believing creates epistemic obligations is not fully convincing

Bilingualism and the single route/dual route debate

The debate between single and dual route accounts of cognitive processes has been generated predominantly by the application of connectionist modeling techniques to two areas of psycholinguistics. This paper draws an analogy between this debate and bilingual language processing. A prominent question within bilingual word recognition is whether the bilingual has functionally separate lexicons for each language, or a single system able to recognize the words in both languages. Empirical evidence has been taken to support a model which includes two separate lexicons working in parallel (Smith, 1991; Gerard and Scarborough, 1989). However, a range of interference effects has been found between the bilingual’s two sets of lexical knowledge (Thomas, 1997a). Connectionist models have been put forward which suggest that a single representational resource may deal with these data, so long as words are coded according to language membership (Thomas, 1997a, 1997b, Dijkstra and van Heuven, 1998). This paper discusses the criteria which might be used to differentiate single route and dual route models. An empirical study is introduced to address one of these criteria, parallel access, with regard to bilingual word recognition. The study fails to find support for the dual route model

On the Similarities Between Native, Non-native and Translated Texts

We present a computational analysis of three language varieties: native, advanced non-native, and translation. Our goal is to investigate the similarities and differences between non-native language productions and translations, contrasting both with native language. Using a collection of computational methods we establish three main results: (1) the three types of texts are easily distinguishable; (2) non-native language and translations are closer to each other than each of them is to native language; and (3) some of these characteristics depend on the source or native language, while others do not, reflecting, perhaps, unified principles that similarly affect translations and non-native language.Comment: ACL2016, 12 page

Exploring the Mental Lexicon of the Multilingual: Vocabulary Size, Cognate Recognition and Lexical Access in the L1, L2 and L3

Recent empirical findings in the field of Multilingualism have shown that the mental lexicon of a language learner does not consist of separate entities, but rather of an intertwined system where languages can interact with each other (e.g. Cenoz, 2013; Szubko-Sitarek, 2015). Accordingly, multilingual language learners have been considered differently to second language learners in a growing number of studies, however studies on the variation in learners’ vocabulary size both in the L2 and L3 and the effect of cognates on the target languages have been relatively scarce. This paper, therefore, investigates the impact of prior lexical knowledge on additional language learning in the case of Hungarian native speakers, who use Romanian (a Romance language) as a second language (L2) and learn English as an L3. The study employs an adapted version of the widely used Vocabulary Size Test (Nation & Beglar, 2007), the Romanian Vocabulary Size Test (based on the Romanian Frequency List; Szabo, 2015) and a Hungarian test (based on a Hungarian frequency list; Varadi, 2002) in order to measure vocabulary sizes, cognate knowledge and response times in these languages. The findings, complemented by a self-rating language background questionnaire, indicate a strong link between Romanian and English lexical proficiency