Sandrine Zufferey

Lexical Pragmatics and Theory of Mind: The Acquisition of Connectives

The concept of theory of mind (ToM), a hot topic in cognitive psychology for the past twenty-five years, has gained increasing importance in the fields of linguistics and pragmatics. However, even though the relationship between ToM and verbal communication is now recognized, the extent, causality and full implications of this connection remain mostly to be explored. This book presents a comprehensive discussion of the interface between language, communication, and theory of mind, and puts forward an innovative proposal regarding the role of discourse connectives for this interface. The proposed analysis of connectives is tested from the perspective of their acquisition, using empirical methods such as corpus analysis and controlled experiments, thus placing the study of connectives within the emerging framework of experimental pragmatics.

Advanced learners' comprehension of discourse connectives: The role of L1 transfer across on-line and off-line tasks

Discourse connectives are important indicators of textual coherence, and mastering them is an essential part of acquiring a language. In this article, we compare advanced learners’ sensitivity to the meaning conveyed by connectives in an off-line grammaticality judgment task and an on-line reading experiment using eye-tracking. We also assess the influence of first language (L1) transfer by comparing learners’ comprehension of two non-native-like semantic uses of connectives in English, often produced by learners due to transfer from French and Dutch. Our results indicate that in an off-line task transfer is an important factor accounting for French- and Dutch-speaking learners’ non-native-like comprehension of connectives. During on-line processing, however, learners are as sensitive as native speakers to the meaning conveyed by connectives. These results raise intriguing questions regarding explicit vs. implicit knowledge in language learners.

Shallow dialogue processing using machine learning algorithms (or not)

This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and several machine learning techniques are used to extract features from dialogue transcripts: maximum entropy classifiers for dialogue acts, latent semantic analysis for topic segmentation, or decision tree classifiers for discourse markers. A rule-based approach is proposed for solving cross-modal references to meeting documents. The methods are trained and evaluated thanks to a common data set and annotation format. The integration of the components into an automated shallow dialogue parser opens the way to multimodal meeting processing and retrieval applications.

Annotating the meaning of discourse connectives in multilingual corpora

Abstract Discourse connectives are lexical items indicating coherence relations between discourse segments. Even though many languages possess a whole range of connectives, important divergences exist cross-linguistically in the number of connectives that are used to express a given relation. For this reason, connectives are not easily paired with a univocal translation equivalent across languages. This paper is a first attempt to design a reliable method to annotate the meaning of discourse connectives cross-linguistically using corpus data. We present the methodological choices made to reach this aim and report three annotation experiments using the framework of the Penn Discourse Tree Bank.

The Role of Perspective Shifts for Processing and Translating Discourse Relations

Previous research has suggested that some discourse relations are easier to convey implicitly than others due to cognitive biases in the interpretation of discourse. In this article we argue that relations involving a perspective shift, such as confirmation relations, are difficult to convey implicitly. We assess this claim with two empirical studies involving the ambiguous French connective en effet, which can either convey a causal relation or a confirmation relation. First, we compare the processing of implicit and explicit causal and confirmation relations conveyed by this connective in a self-paced reading experiment and show that removing the connective in confirmation relations disturbs processing. Second, we compare the percentage of implicit translations of en effet for both discourse relations across three target languages using parallel directional corpora and find that causal relations always lead to more implicit translations than confirmation relations.

Complex syntax in autistic spectrum disorders: A study with relative clauses

BACKGROUND The few studies that have evaluated syntax in autism spectrum disorder (ASD) have yielded conflicting findings: some suggest that once matched on mental age, ASD and typically developing controls do not differ for grammar, while others report that morphosyntactic deficits are independent of cognitive skills in ASD. There is a need for a better understanding of syntax in ASD and its relation to, or dissociation from, nonverbal abilities. AIMS Syntax in ASD was assessed by evaluating subject and object relative clause comprehension in adolescents and adults diagnosed with ASD with a performance IQ within the normal range, and with or without a history of language delay. METHODS & PROCEDURES Twenty-eight participants with ASD (mean age 21.8) and 28 age-matched controls (mean age 22.07) were required to point to a character designated by relative clauses that varied in syntactic complexity. OUTCOMES & RESULTS Scores indicate that participants with ASD regardless of the language development history perform significantly worse than age-matched controls with object relative clauses. In addition, participants with ASD with a history of language delay (diagnosed with high-functioning autism in the DSM-IV-TR) perform worse on subject relatives than ASD participants without language delay (diagnosed with Asperger syndrome in the DSM-IV-TR), suggesting that these two groups do not have equivalent linguistic abilities. Performance IQ has a positive impact on the success of the task for the population with ASD. CONCLUSIONS & IMPLICATIONS This study reveals subtle grammatical difficulties remaining in adult individuals with ASD within normal IQ range as compared with age-matched peers. Even in the absence of a history of language delay in childhood, the results suggest that a slight deficit may nevertheless be present and go undetected by standardized language assessments. Both groups with and without language delay have a similar global performance on relative clause comprehension; however, the study also indicates that the participants with reported language delay show more difficulty with subject relatives than the participants without language delay, suggesting the presence of differences in linguistic abilities between these subgroups of ASD.

Complex Syntax in Autism Spectrum Disorders: A Study of Relative Clauses.

BACKGROUND The few studies that have evaluated syntax in autism spectrum disorder (ASD) have yielded conflicting findings: some suggest that once matched on mental age, ASD and typically developing controls do not differ for grammar, while others report that morphosyntactic deficits are independent of cognitive skills in ASD. There is a need for a better understanding of syntax in ASD and its relation to, or dissociation from, nonverbal abilities. AIMS Syntax in ASD was assessed by evaluating subject and object relative clause comprehension in adolescents and adults diagnosed with ASD with a performance IQ within the normal range, and with or without a history of language delay. METHODS & PROCEDURES Twenty-eight participants with ASD (mean age 21.8) and 28 age-matched controls (mean age 22.07) were required to point to a character designated by relative clauses that varied in syntactic complexity. OUTCOMES & RESULTS Scores indicate that participants with ASD regardless of the language development history perform significantly worse than age-matched controls with object relative clauses. In addition, participants with ASD with a history of language delay (diagnosed with high-functioning autism in the DSM-IV-TR) perform worse on subject relatives than ASD participants without language delay (diagnosed with Asperger syndrome in the DSM-IV-TR), suggesting that these two groups do not have equivalent linguistic abilities. Performance IQ has a positive impact on the success of the task for the population with ASD. CONCLUSIONS & IMPLICATIONS This study reveals subtle grammatical difficulties remaining in adult individuals with ASD within normal IQ range as compared with age-matched peers. Even in the absence of a history of language delay in childhood, the results suggest that a slight deficit may nevertheless be present and go undetected by standardized language assessments. Both groups with and without language delay have a similar global performance on relative clause comprehension; however, the study also indicates that the participants with reported language delay show more difficulty with subject relatives than the participants without language delay, suggesting the presence of differences in linguistic abilities between these subgroups of ASD.

Automatic identification of discourse markers in dialogues: An in-depth study of like and well

Abstract: The lexical items like and well can serve as discourse markers (DMs), but can also play numerous other roles, such as verb or adverb. Identifying the occurrences that function as DMs is an important step for language understanding by computers. In this study, automatic classifiers using lexical, prosodic/positional and sociolinguistic features are trained over transcribed dialogues, manually annotated with DM information. The resulting classifiers improve state-of-the-art performance of DM identification, at about 90% recall and 79% precision for like (84.5% accuracy, @k=0.69), and 99% recall and 98% precision for well (97.5% accuracy, @k=0.88). Automatic feature analysis shows that lexical collocations are the most reliable indicators, followed by prosodic/positional features, while sociolinguistic features are marginally useful for the identification of DM like and not useful for well. The differentiated processing of each type of DM improves classification accuracy, suggesting that these types should be treated individually.

A cross-linguistic perspective on the acquisition of causal connectives and relations

Causality is one of the most frequent coherence relations linking sentences together within texts and discourses, and mastering them is an essential part of acquiring a language. In this paper, we investigate the way French- and Dutch-speaking children acquire these relations depending on the way they are encoded in their mother tongue. From a cross-linguistic perspective, important differences exist in the communication of causal relations. While in some languages like Dutch, objective relations linking causes with consequences and subjective relations linking claims and conclusions are prototypically conveyed by a specific connective, in others like English and spoken French, a single connective is used in both cases. In this paper, we study the impact of these cross-linguistic differences for children’s ability to understand causal relations in a text. Our results indicate that French- and Dutch-speaking children have a similar ability to handle objective and subjective causal relations. In addition, subjective relations remain more difficult than objective relations even at the age of eight. We conclude that conceptual development sets the pace for lexical acquisition and discuss the causes for the acute difficulty of subjective relations.

Discourse connectives: theoretical models and empirical validations in humans and computers

Discourse connectives are procedural markers of textual cohesion that have long been an object of study in the Geneva school of pragmatics. In this chapter, we argue that Jacques Moeschler’s descriptions of causal connectives have contributed to provide theoretical insights on the nature of their procedural meaning, which have been recently shown to be compatible with models of human cognition from processing and acquisition studies across several languages. We review these studies in Sects. 2 and 3 respectively. In many of his contributions, Jacques Moeschler has also strived to find precise and testable features of connectives, with a potential for empirical validations in computer applications. In Sect. 4, we describe recent attempts to label automatically some of the meanings of connectives, using parallel corpora as training data, and show that this procedure improves their translation by automatic systems.