Conversational Context Research Articles

Mitigating Devices within the Context of Two-Way Mediated Shop Conversations

Abstract In this paper, we will present our three-month-long study aimed at investigating the concept of relational language and mitigating devices and how such mitigating devices are used within the context of two-way mediated shop conversations. We will also see how relational language and mitigating devices help speakers establish and maintain good relationship. Our study results show that this relationship is maintained by the avoidance or reduction of unwelcome effects a speech act may have on others within a communication context. The communication context of this paper and the pertaining study are related to the recordings of agent-customer communications in English language. We will show some of the most representative examples found in our corpus and, through those examples, we will be able to see how agents of one telecommunication company in Montenegro1 use different mitigating devices in order to sell a product or a service, entice a customer, or resolve a potentially face-threatening, problematic or volatile situation.

The Use of Illocutionary Speech Acts in Colloquial by Anak Dalam Jambi Tribe

Anak Dalam Jambi Tribe (ADJT) lives in the forest, far from the population, and the existence is rare. This research aims to determine whether ADJT uses illocutionary speech act, function, and type of speech act used. This research uses qualitative with pragmatic research type. The data is in the form of an illocutionary speech act, which is then transcript by putting out the conversation context. This research’s data source is from ADJT, who lives in Merangin Regency, Jambi Province, Indonesia. Result research shows that ADJT uses three types of speech acts, which are (1) directive with the function of prohibiting, ordering, and asking, (2) expressive with the function of thankful, and (3) commissive with the function of refusing. It can be concluded that ADJT frequently uses illocutionary to deliver information to interlocutors. This research is expected can become a preliminary step in further research, especially in the use of language related to indirect meaning in ADJT.

Conversation in small groups: Speaking and listening strategies depend on the complexities of the environment and group

Many conversations in our day-to-day lives are held in noisy environments – impeding comprehension, and in groups – taxing auditory attention-switching processes. These situations are particularly challenging for older adults in cognitive and sensory decline. In noisy environments, a variety of extra-linguistic strategies are available to speakers and listeners to facilitate communication, but while models of language account for the impact of context on word choice, there has been little consideration of the impact of context on extra-linguistic behaviour. To address this issue, we investigate how the complexity of the acoustic environment and interaction situation impacts extra-linguistic conversation behaviour of older adults during face-to-face conversations. Specifically, we test whether the use of intelligibility-optimising strategies increases with complexity of the background noise (from quiet to loud, and in speech-shaped vs. babble noise), and with complexity of the conversing group (dyad vs. triad). While some communication strategies are enhanced in more complex background noise, with listeners orienting to talkers more optimally and moving closer to their partner in babble than speech-shaped noise, this is not the case with all strategies, as we find greater vocal level increases in the less complex speech-shaped noise condition. Other behaviours are enhanced in the more complex interaction situation, with listeners using more optimal head orientations, and taking longer turns when gaining the floor in triads compared to dyads. This study elucidates how different features of the conversation context impact individuals’ communication strategies, which is necessary to both develop a comprehensive cognitive model of multimodal conversation behaviour, and effectively support individuals that struggle conversing.

WHOSE SHAREDPLANS? SCRIPTS, COLLABORATION, AND FEMINIST AI RESEARCH

This paper examines a network of women in AI research who together expanded the range of methodologies and disciplines usually included in AI in the 1980s and 1990s. In particular, Barbara Grosz and Candace Sidner’s concept of $2 offered a way to model conversational context and collaboration in multi-agent AI environments. Drawing on archival work, interviews, conference proceedings, white papers, and departmental reports, I consider the cultural, institutional, and intellectual forces that shaped this network and their research. Using a technofeminist framework (Wajcman 2004; Haraway 1990) and borrowing from Michelle Murphy’s (2012) concept of protocol feminism, this paper examines their “feminist AI protocol.” I outline on one hand an assemblage of techniques, values, methods, and practices that illustrate a protocol rooted in community, interdisciplinarity, and care; these researchers formalized human-computer dialogue as fundamentally collaborative, grounding their approach in the diverse goals and desires of real users. I argue their philosophy of “language as action” mirrors ideas circulating in feminist and critical STS simultaneously. On the other hand, this network of researchers did so from within a particular set of cultural and epistemological parameters of their computer science departments. The research practices of this network offer an opportunity to consider the limits of any feminist AI protocol without a deeper commitment to feminist epistemologies. There remains an urgent need to reflect on how to build feminist AI technologies that make room for and include many different standpoints.

Flouting Maxims in The First Grader (2010) Movie

This study investigated about the flouting of Grice’s maxims in The First Grader movie. This study concerned on finding the types of flouting maxim that occur in the movie and examine the reasons why the characters of The First Grader movie flouted the Grice’s maxims in the dialogue. The present study employs descriptive qualitative research, by analyzing critically each conversation occurr in the movie. The data of the study were in the form of utterances that contained a flouting maxim. The context of conversation in the movie also took a part as the evidence if it is flouting maxims. Implicatures that caused by the speaker is also become the important element in investigated the reason why those maxim are flouted by considering the linguistic context, cultural context, and situational context. The results of the research showed from twenty five utterances that indicated flouting maxim, all types of maxim were flouted in the movie. They were maxim of quantity (18,5%), maxim of quality (22,2%) , maxim of relation (29,6%), and maxim of manner (29,6%). From the finding and analysis, the writers concluded that in several conditions the characters of the movie were flouting the maxims because of some reasons. The major reason that occur in the movie are to give sarcasm, to express angry, and to convince someone.
 Keywords: Cooperative Principle: Flouting maxim: Context of conversation: Implicatures, Movie;

With a little help from familiar interlocutors: real-world language use in young and older adults

Objectives Functional psychologists are concerned with the performance of cognitive activities in the real world in relation to cognitive changes in older age. Conversational contexts may mitigate the influence of cognitive aging on the cognitive activity of language production. This study examined effects of familiarity with interlocutors, as a context, on language production in the real world. Method We collected speech samples using iPhones, where an audio recording app (i.e. Electronically Activated Recorder [EAR]) was installed. Over 31,300 brief audio files (30-second long) were randomly collected across four days from 61 young and 48 healthy older adults in Switzerland. We transcribed the audio files that included participants’ speech and manually coded for familiar interlocutors (i.e. significant other, friends, family members) and strangers. We computed scores of vocabulary richness and grammatical complexity from the transcripts using computational linguistics techniques. Results Bayesian multilevel analyses showed that participants used richer vocabulary and more complex grammar when talking with familiar interlocutors than with strangers. Young adults used more diverse vocabulary than older adults and the age effects remained stable across contexts. Furthermore, older adults produced equally complex grammar as young adults did with the significant other, but simpler grammar than young adults with friends and family members. Conclusion Familiarity with interlocutors is a promising contextual factor for research on aging and language complexity in the real world. Results were discussed in the context of cognitive aging.

Resident impression management within feedback conversations: A qualitative study.

Medical education is moving to conceptualise feedback as a bidirectional learning conversation. Within this conversation, learners experience a tension between assessment and feedback. That perceived tension affects learners' outward performances. In this study, we aimed to characterise residents' experiences with this tension and its effect on learner authenticity within feedback conversations. In this constructivist grounded theory study, the authors were informed by Goffman's theory of impression management. During data analysis, Dweck's theory of mindset was adopted. The authors conducted semi-structured interviews with 15 internal medicine residents. Data collection and analysis were conducted iteratively, using constant comparison to identify themes coinciding with impression management and mindset, ultimately developing a theoretical model to help explain residents' responses to tensions within feedback conversations. Residents constantly felt 'scrutinized', and this affected their engagement in feedback conversations. They staged a performance within those conversations, linked to their underlying mindset: growth or fixed. Growth mindset was characterised by a focus on development as a physician and was associated with asking questions and seeking opportunities for growth. Fixed mindset was characterised by a focus on achieving a favourable evaluation and was associated with a hesitation to ask questions when faced with uncertainty and admit opportunities for growth, because they were concerned about impression management. Context influenced mindset and impression management. Residents adopted a fixed mindset and managed impressions when they perceived the permanence or consequences of evaluations within feedback. Residents adopted a growth mindset when they trusted the supervisor. Residents assess the context of feedback conversations, altering the authenticity of their behaviours. Context, including the perceptions of formal assessment and relationships with supervisors, affected residents' mindset and impression management. Providing space for relationship-building and clarifying the purpose and structure of assessment may be helpful in supporting effective learning conversations in graduate medical education.

Discovering the Fabric of Supportive Conversations: A Typology of Speaking Turns and Their Contingencies

This study examines messages that problem disclosers and supportive listeners enact during conversations about everyday stressors. We coded 402 dyadic interactions between strangers, friends, and romantic couples using Stiles’s (1992) verbal response modes (VRM) and Burleson’s (1982) verbal person centeredness (PC) typology to explore whether (a) listener and discloser utterances coalesce into types of speaking turns, (b) listener turn types vary in person-centered quality, (c) listener turns relate to discloser responses, and (d) discloser responses relate to listener turns. Analyses revealed a typology for both listener and discloser turns: acknowledgment, advisement, question, elaboration, hedged disclosure, and reflection. The relative proportion of those types varied as a function of conversational role and relationship context, and these speech acts varied only minimally in PC. Configural frequency analyses revealed four greater-than-chance contingencies across data sets. The discussion highlights implications for a dyadic and dynamic understanding of supportive communication.

Kierkegaard on Imitation and Ethics: Toward a Secular Project?

AbstractThis essay demonstrates the prominence of imitation in Kierkegaard’s ethics. I move beyond his idea of authentic existence modeled on Christ and explore the secular dimension of Kierkegaard’s insights about human nature and imitation. I start with presenting imitation as key to understanding the ethical dimension of the relationship between the universal and individual aspects of the human self in Kierkegaard. I then show that Kierkegaard’s moral concepts of “primitivity” and “comparison” are a response to his sociological and psychological observations about imitation from an ethical point of view. In the final section of this paper, I briefly engage Friedrich Schleiermacher’s “ethics of individuality” and Gabriel Tarde’s “laws of imitation” to explore Kierkegaard’s consideration of ethics and imitation as situated within the context of a broader conversation on imitation.

Expressive language development in adolescents with Down syndrome and fragile X syndrome: change over time and the role of family-related factors

BackgroundIt is well known that individuals with Down syndrome (DS) or fragile X syndrome (FXS) demonstrate expressive language difficulties beginning early in childhood. It is less clear, however, whether expressive language skills change during the adolescent period in these individuals, and if any of these changes are syndrome specific. Studying this, as well as the role of maternal and family-related factors in expressive language development, may provide the foundation for efficacious interventions for adolescents with DS or FXS.MethodsIn this study, we examined expressive language trajectories, assessed through conversation and narration, in 57 adolescent males with intellectual disability (ID) (20 DS and 37 FXS) in relation to the diagnostic group (DS vs. FXS) and family-related factors (maternal IQ, maternal psychological distress, closeness in the mother–child relationship, family income, and maternal and paternal education) after adjusting for chronological age (CA) and nonverbal cognition.ResultsChanges over repeated annual assessments for males with DS or FXS were observed only during conversation, such as an increase in talkativeness, but a decrease in syntax complexity and lexical diversity. We found a diagnosis-related effect in the change over time in conversational talkativeness favoring those with FXS. Finally, a closer mother–child relationship predicted less decrease over time in lexical diversity during conversation, and participants of mothers who graduated college showed a greater increase in conversational talkativeness over time compared to those of mothers with a high school education.ConclusionsOur results suggest that, during the adolescent period for males with DS or FXS, there is an increase in the amount of talk produced in conversational contexts, but also a decrease in the quality of the language produced. In addition, our results indicate syndrome-specificity for aspects of expressive language development and reinforce the protective role of family-related factors.

Transitive Topic Modeling with Conversational Structure Context: Discovering Topics that are Most Popular in Online Discussions

With the explosive growth of online discussions published everyday on social media platforms, comprehension and discovery of the most popular topics have become a challenging problem. Conventional topic models have had limited success in online discussions because the corpus is extremely sparse and noisy. To overcome their limitations, we use the discussion thread tree structure and propose a “popularity” metric to quantify the number of replies to a comment to extend the frequency of word occurrences, and the “transitivity” concept to characterize topic dependency among nodes in a nested discussion thread. We build a Conversational Structure Aware Topic Model (CSATM) based on popularity and transitivity to infer topics and their assignments to comments. Experiments on real forum datasets are used to demonstrate improved performance for topic extraction with six different measurements of coherence and impressive accuracy for topic assignments.

This paper might change your mind

AbstractLinguistic intervention in rational decision making is standardly captured in terms of information change. But the standard view gives us no way to model interventions involving expressions that only have an attentional effects on conversational contexts. How are expressions with non‐informational content – like epistemic modals – used to intervene in rational decision making? We show how to model rational decision change without information change: replace a standard conception of value (on which the value of a set of worlds reduces to values of individual worlds in the set) with one on which the value of a set of worlds is determined by a selection function that picks out a generic member world. We discuss some upshots of this view for theorizing in philosophy and formal semantics.

Culturally Sustaining Pedagogies in the Current Moment: A Conversation With Django Paris and H. Samy Alim

AbstractThis department explores how teachers can sustain students’ multilingual literacies and reimagine literacy learning across multiple contexts in conversation with researchers, practitioners, and communities.

Google Mini: Italian Example of Artificial Prosociality

Prosociality is a social and individual virtue, which evokes mixed feelings in the modern world. Generally, prosociality behavior is defined as “actions taken for the benefit of one or more other persons” (Wispe, 1972). The Digital Revolution and the birth of artificial intelligence, such as the Google Mini, allowed the transition from elitist experience to mass experience. The study has an exploratory function and starts from the Man-AI interaction, in a provocative and oppositional conversational context created by the Human Being. In the research, it is hypothesized, therefore, that the synthesis of the artificial voice does not allow to characterize all the facets of the tone and the emotionality of the prosociality. As a result, Artificial Intelligence is programmed to always respond in a “gentle” way, putting in place different facets of prosociality, which are well detected in the emotionality and prosodic analysis, above all in the recognition of “pitch” speech pattern. While emotional tone analysis confirms the “understanding” of reading the communicative context of Artificial Intelligence. Among future perspectives it is highlighted how the study of these vocal patterns of artificial prosociality can be a springboard for research on bullying, using the Google Mini Prosocial tool.

The use of specific linguistic features within the context of a casual conversation in a speech community

There seems to be nothing remarkable about the interaction between two interlocutors who have never been in contact with each other. These persons are able to understand themselves in contact situations because most times, a common language of communication is known that can sustain the exchange for the time necessary. However, when such exchange is between individuals with some level of contact or familiarity, the concept of speech community comes into play. The concept is useful but may be problematic at times and one cannot avoid applying this idea when trying to make sense of the process that takes place in the conversation, specifically a causal conversation. The aim of this sociolinguistic study is to explain how individuals are able to build social history, construct interactional talk, maintain relations with each other and reinforce solidarity from a two hour audio recorded conversation (ARC) between an ethnic Indian and a Nigerian in Marylebone, London using interactional socio-linguistic and conversation analytic. By doing so, the concept of a speech community as well as how a group can be identified as being members of a community is understood. A particular focus is paid to such linguistic features as the register of conversation, turn taking, discourse variation, phonological variation and grammatical variation characteristic of London, Nigerian and Indian English observed in the speech of the participants and how these features function to build and maintain relations.
 Keywords: Speech community, Casual conversation, Linguistic features, Sociolinguistics, ARC

Transfer learning meets sales engagement email classification: Evaluation, analysis, and strategies

AbstractEnterprise email classification in the sales engagement platform is a challenge due to its evolving asynchronous conversational context during the sales process and differences across industries and organizations. This is further exacerbated by the limited amount of labeled emails due to security and privacy constraints. The leaderboard success of using pretrained language models (LMs) such as BERT and various transfer learning techniques promises a paradigm shift to natural language processing, yet the recipe for applying high performance transfer learning (HPTL) in practical applications remains unclear. This article investigates applying HPTL to sales engagement email classification through a series of experiments and analysis. The experiment datasets include two different organizations' emails. The contribution of this paper is 4‐fold: (a) analysis and characterization of the email corpora from different organizations; (b) identification of the best combinations of pre‐trained LMs under different modeling architectures; (c) study of the impact and trade‐off of limited labeled data on the model accuracy and training time; and (d) characterization and study of the impact of different orgs' datasets on the model accuracy. Our results showed that a practical winning recipe that uses BERT‐finetuning with as few as 500 labeled training examples can consistently outperform significantly with reasonable training time among all models evaluated.

Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation

Background Based Conversation (BBCs) have been introduced to help conversational systems avoid generating overly generic responses. In a BBC, the conversation is grounded in a knowledge source. A key challenge in BBCs is Knowledge Selection (KS): given a conversational context, try to find the appropriate background knowledge (a text fragment containing related facts or comments, etc.) based on which to generate the next response. Previous work addresses KS by employing attention and/or pointer mechanisms. These mechanisms use a local perspective, i.e., they select a token at a time based solely on the current decoding state. We argue for the adoption of a global perspective, i.e., pre-selecting some text fragments from the background knowledge that could help determine the topic of the next response. We enhance KS in BBCs by introducing a Global-to-Local Knowledge Selection (GLKS) mechanism. Given a conversational context and background knowledge, we first learn a topic transition vector to encode the most likely text fragments to be used in the next response, which is then used to guide the local KS at each decoding timestamp. In order to effectively learn the topic transition vector, we propose a distantly supervised learning schema. Experimental results show that the GLKS model significantly outperforms state-of-the-art methods in terms of both automatic and human evaluation. More importantly, GLKS achieves this without requiring any extra annotations, which demonstrates its high degree of scalability.

Modality-Balanced Models for Visual Dialogue

The Visual Dialog task requires a model to exploit both image and conversational context information to generate the next response to the dialogue. However, via manual analysis, we find that a large number of conversational questions can be answered by only looking at the image without any access to the context history, while others still need the conversation context to predict the correct answers. We demonstrate that due to this reason, previous joint-modality (history and image) models over-rely on and are more prone to memorizing the dialogue history (e.g., by extracting certain keywords or patterns in the context information), whereas image-only models are more generalizable (because they cannot memorize or extract keywords from history) and perform substantially better at the primary normalized discounted cumulative gain (NDCG) task metric which allows multiple correct answers. Hence, this observation encourages us to explicitly maintain two models, i.e., an image-only model and an image-history joint model, and combine their complementary abilities for a more balanced multimodal model. We present multiple methods for this integration of the two models, via ensemble and consensus dropout fusion with shared parameters. Empirically, our models achieve strong results on the Visual Dialog challenge 2019 (rank 3 on NDCG and high balance across metrics), and substantially outperform the winner of the Visual Dialog challenge 2018 on most metrics.

Mask & Focus: Conversation Modelling by Learning Concepts

Sequence to sequence models attempt to capture the correlation between all the words in the input and output sequences. While this is quite useful for machine translation where the correlation among the words is indeed quite strong, it becomes problematic for conversation modelling where the correlation is often at a much abstract level. In contrast, humans tend to focus on the essential concepts discussed in the conversation context and generate responses accordingly. In this paper, we attempt to mimic this response generating mechanism by learning the essential concepts in the context and response in an unsupervised manner. The proposed model, referred to as Mask & Focus maps the input context to a sequence of concepts which are then used to generate the response concepts. Together, the context and the response concepts generate the final response. In order to learn context concepts from the training data automatically, we mask words in the input and observe the effect of masking on response generation. We train our model to learn those response concepts that have high mutual information with respect to the context concepts, thereby guiding the model to focus on the context concepts. Mask & Focus achieves significant improvement over the existing baselines in several established metrics for dialogues.

VALIDITAS DAN RELIABILITAS TES MELENGKAPI WACANA PADA PENELITIAN PRAGMATIK BAHASA ANTARA (INTERLANGUAGE PRAGMATICS)

This article is intended to provide insight to researchers who are still doubtful about the validity and reliability of one of the data collection methodologies, namely the method of discourse completion test in general pragmatic research and interlanguage pragmatics. The literature review was used in the preparation of this article to get the comprehensive picture of the completion discourse test. One of the results is that data collection methods using completion discourse test have advantages and disadvantages. One drawback is that the authenticity of the data and the limitations on the data quality obtained from an informant or respondent, even in certain studies, is judged to not be able to capture sufficiently good data. However, this method is a very good method to find stereotype data because researchers can obtain abundant data in sufficient quantities by this method. In addition, this completion discourse test is very effective in the language study in the cross-cultural domain. This method can be used to capture data in two or more languages with different cultural backgrounds as Blum-Kulka and Olshtain did (in 1984). The control of research variables by using the completion discourse test is considered better because one of the research variables in pragmatic studies is the context of conversation which is very dynamic so that there needs to be controlled. Controlling this research variable is expected to be able to make conclusions that are more conical answer for the research problem. Keywords: discourse completion test, interlanguage pragmatics, research variable control