Relevant bibliographies by topics / Conversation

Academic literature on the topic 'Conversation'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Conversation"

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Rahayu, Endry Sri Rahayu Sri, and Safnil . "TYPES OF IMPLICATURE IN INFORMAL CONVERSATIONS USED BY THE ENGLISH EDUCATION STUDY PROGRAM STUDENTS." JOALL (Journal of Applied Linguistics & Literature) 1, no. 1 (February 4, 2018): 65–83. http://dx.doi.org/10.33369/joall.v1i1.3942.

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Implicature was refers to implied meaning in utterance that can be understood by indirectly expression. In informal conversation was occurred the hidden meaning of what actually said by the speakers. This study was investigated the types of implicature in informal conversations used by the English education study program students. The study was aimed to analyze the types of implicature and how the implicature is carried out in the informal conversations. The method of study was a descriptive qualitative method. The subjects of this study were 25 students of English study program who have informal conversation. The students’ conversation was transcribed and analyzed by using checklist instrument. The results was shown that 1) there were three types of implicature found in the informal conversations; conventional implicature, generalized conversational implicature and particularized conversational implicature, and 2) the implicature is carried out in the informal conversations by the used of generalized conversational implicature and particularized conversational implicature. Moreover, a conclusion is students in the informal conversation have potentially implicature that indicates that their utterance has implied meaning. The suggestions, the study about implicature should be conducted in different area such as movie, drama or others, to give enrichment information in the Pragmatics study.
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Musa, Rabab Elsheikh Idris, and Bahia K. Mohammed. "The Role of Conversational Implicature in Daily Conversations – What Matters, Content or Context?" Theory and Practice in Language Studies 12, no. 5 (May 4, 2022): 886–93. http://dx.doi.org/10.17507/tpls.1205.08.

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In daily conversation, sometimes dialogue includes terms that vary entirely from the common phrases. From a linguistic perspective, the conversational implicatures are the speaker's intended meaning of the utterance. Conversation implications are the specific conversations between the speaker and the receiver by following the communications principles. It is the most significant component that has undergone argumentation in conversation theory. Grice's theory of dialogue inference is the possibility of providing meaning to the literal. In other words, people apply certain cooperative principles to communicate cooperatively. Thus, conversational implicatures have become one of the top research areas in pragmatics. This paper intends to explore the importance of conversational implicatures in day-to-day conversations in various contexts. It focuses on certain dialogues collected and integrated from the routine conversation. The outcome revealed that context plays a vital role in interpreting utterances. Therefore, there is no possibility of a complete correspondence of one utterance to one context, which shows the conversational implicature cannot be context-independent. In addition, dialogues were classified into Generalized, Scalar, and Particular conversational implicatures.
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Wylie, Karen, Hayley M. Carrier, Andreas M. Loftus, Ramishka Thilakaratne, and Naomi Cocks. "Barriers and Facilitators to Conversation: A Qualitative Exploration of the Experiences of People with Parkinson’s and Their Close Communication Partners." Brain Sciences 12, no. 7 (July 19, 2022): 944. http://dx.doi.org/10.3390/brainsci12070944.

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Conversations are an important part of our daily lives, enabling us to interact with others and participate in a range of activities. For people with Parkinson’s, conversation can be challenging when communication is impacted. This qualitative exploratory study investigated the experiences of people with Parkinson’s and their close communication partners in conversations. The study explored influences on conversational participation, considering perceived barriers and facilitators to participation in conversation for people with Parkinson’s. Interviews were conducted with eight dyads, with participants interviewed both jointly and separately (24 interviews). Five themes revealed that conversation appears to be influenced not only by the communication skills of the person with Parkinson’s, but also by factors associated with the communication partner, the complex nature of conversations, the communication environment, and the impact of experience in shaping participation in conversation. Specific barriers and facilitators to conversational participation were identified. This study offers important insight into the lived experience of people with Parkinson’s affected by communication difficulties. The findings support the notion that it is more than simply the communication skills of the person with Parkinson’s that influence conversations. It is important that other factors influencing conversational success should be included in interventions supporting communication for people with Parkinson’s.
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Anggrarini, Natalia. "CONVERSATIONAL IMPLICATURE ANALYSIS OF TEXT MESSAGE BETWEEN NATIVE SPEAKR AND FOREIGN LANGUAGE SPEAKER OF ENGLISH." Wiralodra English Journal 1, no. 1 (September 8, 2017): 59–73. http://dx.doi.org/10.31943/wej.v1i1.17.

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In this global era, it is possible to do communication with native speaker of English. Thus, the need to master communicative competence of English communication is needed. Beside face to face communication, people are also need to be able to communicate in different way, such as chat via mobile phone. It is used to call as Short Message Service or SMS. This study is aimed to know the kinds of conversation that happened in their short text message for a month. The classification of conversation is according to the Grice (1975) the formulation of Cooperative Principle in which it is classified into Generalized Conversation Implicature and Particularized Conversational Implicature. The method used in this study is Descriptive Qualitative. It is used to interpret the data according to the conversational classification. The result of this study shows that 81. 25 % the conversations are classified into Generalized Conversational Implicature, and 18. 75% conversations are classified into Particularized Conversational Implicature.
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Fakhriani, Zummia. "Hasan Minhaj’s Spontaneous Conversational Humor in Patriot Act." Journal of Literature, Linguistics, & Cultural Studies 2, no. 1 (July 24, 2023): 194–205. http://dx.doi.org/10.18860/lilics.v2i1.2905.

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Grice's maxim of conversation becomes the main condition for a complete and ideal conversation. Spontaneous conversational humor is used in communicating with others, in light conversations with relatives, and in a broader public space, such as television shows and radio broadcasts. This linguistic phenomenon is often used as a speaker strategy in criticizing an action of an individual that is distorted but narrated in the form of humor that invites the audience's laughter. The researcher analysed Hasan Minhaj’s and his audience's spontaneous conversational humor in this study. Methodologically, the researcher adopted Grice's pragmatics study on the Theory of Cooperative Principle (1975), which aimed to make conversations cooperative. The researcher collected the data from Hasan Minhaj and his audience's utterances from September 2, 2019, to November 11, 2019. 21 data in the form of spoken transcripts containing spontaneous conversational humor, analysed by Martin's theory of spontaneous humor categorization (2007), which also contained non-observances (floating) based on the principle of conversation proposed by Grice (1975). The results showed that Hasan Minhaj deliberately and spontaneously expressed humorous conversations on his TV show "Patriot Act", which flouted the cooperative principle in conversation (Grice, 1975). The spontaneous conversational humor outlined by Hasan Minhaj in a broad outline showed that it aimed to criticize and comment on government policies that had violated the rights of the citizens. This study significantly contributed to expanding spontaneous conversational humor studies in linguistics.
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Joty, S., G. Carenini, and R. T. Ng. "Topic Segmentation and Labeling in Asynchronous Conversations." Journal of Artificial Intelligence Research 47 (July 22, 2013): 521–73. http://dx.doi.org/10.1613/jair.3940.

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Topic segmentation and labeling is often considered a prerequisite for higher-level conversation analysis and has been shown to be useful in many Natural Language Processing (NLP) applications. We present two new corpora of email and blog conversations annotated with topics, and evaluate annotator reliability for the segmentation and labeling tasks in these asynchronous conversations. We propose a complete computational framework for topic segmentation and labeling in asynchronous conversations. Our approach extends state-of-the-art methods by considering a fine-grained structure of an asynchronous conversation, along with other conversational features by applying recent graph-based methods for NLP. For topic segmentation, we propose two novel unsupervised models that exploit the fine-grained conversational structure, and a novel graph-theoretic supervised model that combines lexical, conversational and topic features. For topic labeling, we propose two novel (unsupervised) random walk models that respectively capture conversation specific clues from two different sources: the leading sentences and the fine-grained conversational structure. Empirical evaluation shows that the segmentation and the labeling performed by our best models beat the state-of-the-art, and are highly correlated with human annotations.
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Daraškienė, Inga, and Inga Hilbig. "Conversational strategies in children’s talk." Taikomoji kalbotyra, no. 12 (January 15, 2019): 1–38. http://dx.doi.org/10.15388/tk.2019.17231.

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The aim of this article is to investigate linguistic and non-linguistic conversational strategies and their realisations, employed by five year olds in peer interactions. 5 hours and 49 minutes of recorded children’s talk were used for the analysis. The data were processed using Transana software, and qualitative conversation analysis was applied. The analysis reveals that children are more inclined to use conversational strategies that motivate cooperation and solidarity rather than competition or dominance in a conversation. Dialogues mostly involve comments and questions, followed by repetitions of both speaker’s own or the interlocutor’s words. Jokes are also used to maintain or restart conversations and to support or restore friendly relationships. Strategies that break the symmetry of conversation are rarely applied. The conversation is sometimes interrupted when opposing the partner or establishing a leader role. Silence as a conversation strategy also serves to communicate disagreement with partner’s statements. Overall, the research subjects appear to be pragmatically competent interlocutors, adhering to the main principles of adult conversation: able to wait for their turn in conversation, choose and change its topic appropriately, involve the interlocutor in it or regain his/her attention if needed, and solve communicational break-downs and conflicts. However, the results presented are to be confirmed by further studies and through more various child-to-child conversations.
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Kim, Yeo Jin, Hye Yeong Jeong, Hui-Chul Choi, Jong-Hee Sohn, Chulho Kim, Sang-Hwa Lee, Joon Soo Shin, et al. "Effect of right hemispheric damage on structured spoken conversation." PLOS ONE 17, no. 8 (August 11, 2022): e0271727. http://dx.doi.org/10.1371/journal.pone.0271727.

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Patients with right hemisphere damage (RHD) occasionally complain of difficulties in conversation. A conversation is a type of communication between the speaker and listener, and several elements are required for a conversation to take place. However, it is unclear which of those elements affect communication in patients with RHD. Therefore, we prospectively enrolled 11 patients with right hemispheric damage due to acute cerebral infarction, within 1 week of onset. To evaluate patients’ conversational abilities, we used a structured conversation task, namely, the “Hallym Conversation and Pragmatics Protocol”. The topics of conversation were “family”, “leisure”, and “other/friends”. The conversation characteristics were classified according to three indices: the “conversational participation index”, “topic manipulation index”, and “conversational breakdown index”. Patients with RHD were compared with 11 age-, sex-, and years of education-matched healthy adults. The most common site of damage in the patients with RHD was the periventricular white matter. There was no significant difference in performance between the two groups according to the conversation participation index and in the discontinuance rate assessed with the conversational breakdown index. However, patients with RHD showed a lower topic maintenance rate and higher topic initiation and topic switching rates, according to the topic manipulation index. Therefore, we explored the characteristics of impaired conversation abilities in patients with RHD by assessing their ability to converse and manage topics during structured conversations, and found difficulties with pragmatics and communication discourse in these patients.
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Widiyati, Elok. "THE FEATURES OF INTERRUPTING, COLLABORATING, AND BACKCHANNELLING USED BY BROADCASTER AND CALLER IN TELEPHONE CONVERSATION." EduLite: Journal of English Education, Literature and Culture 1, no. 1 (February 1, 2016): 1. http://dx.doi.org/10.30659/e.1.1.1-16.

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Conversational analysis is a part of conversational structure that manages people's communication. It deals with pragmatics. Some of the conversational structures consist of features in interrupting, collaborating, and backchannelling (Celce-Murcia, 1995: 14). This research was intended to analyze how the three features were applied in the English conversation by broadcasters and callers in English Corner Program. This research was qualitative. The data consisted of eight conversations. The data were collected through the following steps: recording, transcribing, selecting, and reporting. Then, they were analyzed with conversational approach drawn on Celce Murcia (1995). It was revealed that the broadcasters and callers in the eight conversations used the features of interrupting, collaborating, and backchanneling. They did not fully perform common English expressions and gambits. However, they tended to perform the simpler and easier ones. This implied that the participants have not known the appropriate expressions. Based on the result of this research, it was concluded that the conversations in this study were less structured and patterned. It was suggested for the readers who learn about conversational structure, that they should pay attention not only to the linguistic components, but also the pragmatics in which the English conversation takes place, including participant, context, and topic of a conversation.
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Abbas, Irfan, Khalid Ahmed, and Muhammad Asad Habib. "Conversation Analysis: A Methodology for Diagnosing Autism." Global Language Review VII, no. II (June 30, 2022): 1–12. http://dx.doi.org/10.31703/glr.2022(vii-ii).01.

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The present study examines the conversational turn-taking patterns in autist-neurotypical talk. The objective of the study is to find out the distinctive features of autist-normal conversations. This study is cross-sectional, descriptive and qualitative in its nature. Recordings are done in anautism center in Lahore for a period of ten days. It is mainly a qualitative study in its nature. Five autistic children of different ages are selected from an autism center in Lahore. The data for the study is collected through video recording of the conversations between autists and speech therapists. The sample is selected through convenient sampling and analysis is done by following the methods of conversation analysis. The results of the analysis highlight certain distinct features of autist child-therapist talk which are not observed in the normal ordinary conversation. However, there is not a total violation of the conversation rules on the part of autists. Moreover, the findings of the research show that conversational patterns in autist-normal conversation are also affected by the chronological age of the autists. Finally, the research concludes that conversation analysis can be used as a tool for the identification of autism.
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Dissertations / Theses on the topic "Conversation"

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Wilson, J. "Conversational matters : Towards a theory of everyday conversation." Thesis, Queen's University Belfast, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.374222.

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Ishii, Ryo. "Designing Conversational Interfaces for Facilitating Conversation using User's Gaze Behaviors." 京都大学 (Kyoto University), 2013. http://hdl.handle.net/2433/180472.

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Caron, Melinda. "Conversation intime et pédagogie dans Les conversations d'Émilie de Louise d'Épinay." Thesis, Université Laval, 2003. http://www.theses.ulaval.ca/2003/20994/20994.pdf.

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Dans Les Conversations d’Émilie (1782), Louise d’Épinay, femme de lettres des Lumières liée au milieu encyclopédique, propose un modèle d’éducation féminine s’incarnant dans une série de vingt dialogues inspirés des conversations pédagogiques qu’elle a partagées avec sa petite fille Émilie. S’appropriant, dans cette œuvre testamentaire, la structure de la conversation philosophique pour l’éducation d’une fillette et ancrant cette structure dans un cadre intime, elle offre une solution de compromis permettant aux femmes un accès à une formation morale et intellectuelle alliant bonheur et utilité sociale. L’intimité devient le terrain d’élection d’une pensée qui cherche son dépassement dans la transmission générationnelle de son modèle pédagogique et son prolongement dans un espace d’amitié et d’intellectualité féminines. Porteur, en point de mire, d’une réforme des possibilités sociales pour les femmes, le modèle de Louise d’Épinay, grâce à sa forme dialogique, s’inscrit pleinement dans ce que l’on pourrait appeler les « Lumières au féminin. »
Inscrite au Tableau d'honneur de la Faculté des études supérieures
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Caron, Mélinda. "Conversation intime et pédagogie dans Les conversations d'Émilie de Louise d'Épinay." Master's thesis, Université Laval, 2003. http://hdl.handle.net/20.500.11794/17848.

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Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2003-2004
Dans Les Conversations d'Émilie (1782), Louise d'Épinay, femme de lettres des Lumières liée au milieu encyclopédique, propose un modèle d'éducation féminine s'incarnant dans une série de vingt dialogues inspirés des conversations pédagogiques qu'elle a partagées avec sa petite fille Émilie. S'appropriant, dans cette œuvre testamentaire, la structure de la conversation philosophique pour l'éducation d'une fillette et ancrant cette structure dans un cadre intime, elle offre une solution de compromis permettant aux femmes un accès à une formation morale et intellectuelle alliant bonheur et utilité sociale. L'intimité devient le terrain d'élection d'une pensée qui cherche son dépassement dans la transmission générationnelle de son modèle pédagogique et son prolongement dans un espace d'amitié et d'intellectualité féminines. Porteur, en point de mire, d'une réforme des possibilités sociales pour les femmes, le modèle de Louise d'Épinay, grâce à sa forme dialogique, s'inscrit pleinement dans ce que l'on pourrait appeler les "Lumières au féminin"
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Cowne, Elizabeth Ann. "Conversational uses of the repertory grid for personal learning and the management of change in special educational needs." Thesis, Brunel University, 1994. http://bura.brunel.ac.uk/handle/2438/5095.

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An action research design, incorporating the repertory grid as a framework for Learning Conversations, is used to examine the management of change for a group of teachers and their schools. The study sets out to analyse how individual, teachers, from twelve primary and middle schools, in three outer London boroughs, learnt about managing change in their schools, in relation to children with Special Educational Needs. To study how the school supported these individuals, Headteachers and Deputy Heads were also included in the research. The sample of teachers was chosen from those who had attended either of two sets of in-service courses on Special Educational Needs in Ordinary Schools. The first set of teachers had recently completed their course; the second had completed courses between five and eight years previously. This gave an opportunity to compare short-term and long-term learning outcomes from these courses. As the study progressed, so did the development of the use of the conversational techniques. Flexible Learning Conversations, which went beyond the repertory grid techniques, were developed, and the evidence showed that this improved individuals' ability to reflect on their work, thus gaining confidence for future action in their schools. It was, also possible to develop a procedure for small groups of participants to share their own constructs, elicited from personal grid conversations. This led, into a Group Learning Conversation, which also included future action planning. The research also examines the interaction of action research and the Learning Conversation using the repertory grid, in helping to develop reflective practitioners and effective schools. As co-ordinating tutor for both sets of in-service courses, as a co-ordinator of LEA support services in two of the LEAs, and in the role as action researcher, my personal learning has formed part of the research outcomes.
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Wall, Marie Lala. "A conversation." Thesis, Virginia Polytechnic Institute and State University, 1991. http://hdl.handle.net/10919/53309.

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Fujimura-Wilson, Kayo. "A sociolinguistic study of Japanese conversation : analysis of three conversational features." Thesis, Birkbeck (University of London), 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.424931.

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Nakatsuhara, Fumiyo. "Conversational styles in group oral tests : how is the conversation co-constructed?" Thesis, University of Essex, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.499803.

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Brassac, Christian. "S'engager en conversation : étude expérimentale de l’engagement illocutoire en conversation." Nancy 2, 1992. http://www.theses.fr/1992NAN21009.

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Forme prototypique de l'interaction verbale, la conversation repose en grande partie sur des significations non littérales. La question traitée est celle du lien qu'entretient le locuteur à un certain type d'acte de langage non littéral : l'implicitation conversationnelle. La théorie de l'engagement illocutoire (Daniel Vanderveken, 1988), issue de la philosophie du langage, propose des concepts théoriques permettant d'opérationnaliser cette question. Une expérimentation reposant sur ces notions et sur un critère d'incohérence d'un locuteur niant l'acte non littéral concerné produit des résultats significatifs quant à l'engagement du locuteur sur ces implicitations conversationnelles: en particulier l'aspect graduel de cet engagement est mis en évidence, plus généralement, ce travail s'inscrit dans un ensemble d'études visant a utiliser les notions de la théorie des actes de langage en analyse des conversations
As a prototypical form of verbal interaction, conversation is mainly based on non literal meanings. The problem at issue focuses on the link between the speaker and a certain type of non literal speech act: the conversational implicatures: the theory of illocutionary commitment (Daniel Vanderveken, 1985). Born of the philosophy of language, provides concepts which allow to make this question operational. An experience, based on these notions and on a criterion of incoherence of a speaker who denies the non literal speech act concerned, produces significant results on the speaker's commitment to these conversational implicatures, to the more precise, the gradual aspect of this commitment is put forward. More generally, this work contributes to a set of studies aimed to use notions of speech acts' theory in discourse analysis
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Clift, Rebecca Jane. "Misunderstandings in conversation." Thesis, University of Cambridge, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242958.

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Books on the topic "Conversation"

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Givón, T., ed. Conversation. Amsterdam: John Benjamins Publishing Company, 1997. http://dx.doi.org/10.1075/tsl.34.

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Lois, Arthur, ed. Conversation. Oxford: ELBS with Oxford University Press, 1991.

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Zeldin, Theodore. Conversation. London: Harvill, 1998.

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Lois, Arthur, ed. Conversation. Oxford: Oxford University Press, 1987.

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author, Thirlwell Adam 1978, ed. Conversation. Porto]: Serralves, 2017.

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Strong, Kalmia. [Conversation]. [Iowa City, Iowa]: [The artist], 2014.

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Keane, Molly. Conversation piece. London: Virago Press, 1991.

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Lerner, Gene H., ed. Conversation Analysis. Amsterdam: John Benjamins Publishing Company, 2004. http://dx.doi.org/10.1075/pbns.125.

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Drew, Paul, and John Heritage. Conversation Analysis. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Ltd, 2006. http://dx.doi.org/10.4135/9781446261156.

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Hsieh, Bata. English conversation. Taiwan: Cai Zu, 2003.

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Book chapters on the topic "Conversation"

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Rolston, Imara Ajani. "A Conversation About Conversations." In The Politics of Cultural Knowledge, 121–36. Rotterdam: SensePublishers, 2011. http://dx.doi.org/10.1007/978-94-6091-481-2_10.

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Kremer, Robert, and Roberto Flores. "Policies, Conversations, and Conversation Composition." In Advances in Artificial Intelligence, 50–58. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18356-5_5.

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Hydén, Lars-Christer, Anna Ekström, and Ali Reza Majlesi. "Conversations Without Words: Proto-Conversation." In Living with Late-Stage Dementia, 213–30. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56870-1_10.

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Guissin-Stubbs, Tara. "Conversation." In The Modern Irish Sonnet, 113–56. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53242-0_4.

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Searle, John R. "Conversation." In (On) Searle on Conversation, 7. Amsterdam: John Benjamins Publishing Company, 1992. http://dx.doi.org/10.1075/pbns.21.02sea.

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Bojesen, Emile. "Conversation." In Forms of Education, 112–22. Abingdon, Oxon ; New York, NY : Routledge, 2020.: Routledge, 2019. http://dx.doi.org/10.4324/9781351060677-10.

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Fujishin, Randy. "Conversation." In Natural Bridges in Interpersonal Communication, 115–37. Second edition. | London ; New York : Routledge, 2020. | Revised edition of: Natural bridges : a guide to interpersonal communication / Randy Fujishin. c2012.: Routledge, 2019. http://dx.doi.org/10.4324/9780429196935-6.

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Agboaye, Isi. "Conversation." In The Routledge Companion to Applied Performance, 84–94. Abingdon, Oxon ; New York : Routledge 2021. |: Routledge, 2020. http://dx.doi.org/10.4324/9781003088042-14.

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Druin, Allison, and Jon Kolko. "Conversation." In Participatory Design for Learning, 189–201. New York, NY : Routledge, 2017.: Routledge, 2017. http://dx.doi.org/10.4324/9781315630830-18.

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Rogers, Yvonne, Christopher Frauenberger, and Chris Quintana. "Conversation." In Participatory Design for Learning, 225–34. New York, NY : Routledge, 2017.: Routledge, 2017. http://dx.doi.org/10.4324/9781315630830-22.

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Conference papers on the topic "Conversation"

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Zhang, Dong, Liangqing Wu, Changlong Sun, Shoushan Li, Qiaoming Zhu, and Guodong Zhou. "Modeling both Context- and Speaker-Sensitive Dependence for Emotion Detection in Multi-speaker Conversations." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/752.

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Recently, emotion detection in conversations becomes a hot research topic in the Natural Language Processing community. In this paper, we focus on emotion detection in multi-speaker conversations instead of traditional two-speaker conversations in existing studies. Different from non-conversation text, emotion detection in conversation text has one specific challenge in modeling the context-sensitive dependence. Besides, emotion detection in multi-speaker conversations endorses another specific challenge in modeling the speaker-sensitive dependence. To address above two challenges, we propose a conversational graph-based convolutional neural network. On the one hand, our approach represents each utterance and each speaker as a node. On the other hand, the context-sensitive dependence is represented by an undirected edge between two utterances nodes from the same conversation and the speaker-sensitive dependence is represented by an undirected edge between an utterance node and its speaker node. In this way, the entire conversational corpus can be symbolized as a large heterogeneous graph and the emotion detection task can be recast as a classification problem of the utterance nodes in the graph. The experimental results on a multi-modal and multi-speaker conversation corpus demonstrate the great effectiveness of the proposed approach.
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Yan, Rui, and Dongyan Zhao. "Smarter Response with Proactive Suggestion: A New Generative Neural Conversation Paradigm." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/629.

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Conversational systems are becoming more and more promising by playing an important role in human-computer communications. A conversational system is supposed to be intelligent to enable human-like interactions. The long-term goal of smart human-computer conversations is challenging and heavily driven by data. Thanks to the prosperity of Web 2.0, a large volume of conversational data become available to establish human-computer conversational systems. Given a human issued message, namely a query, a traditional conversational system would provide a response after proper training of how to respond like humans. In this paper, we propose a new paradigm for neural generative conversations: smarter response with a suggestion is provided given the query. We assume that the new conversation mode which proactively introduces contents as next utterances, keeping user actively engaged. To address the task, we propose a novel integrated model to handle both the response generation and the suggestion generation. From the experimental results, we verify the effectiveness of the new neural generative conversation paradigm.
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Yamagata, Koichi, Koya Kawahara, Yuto Suzuki, Yuki Nakahodo, Shunsuke Ito, Haruka Matsukura, and Maki Sakamoto. "Neural Network Model for Visualization of Conversational Mood with Four Adjective Pairs." In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004396.

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In recent years, the accuracy of speech recognition has improved remarkably. Speech recognition software can be used to obtain text information from conversational speech data. Although text can be treated as surface level information, several studies have indicated that speech recognition can also be used to estimate emotions, which represent higher level information in a conversation. Several newly proposed models use LSTM or GRU to estimate emotion in conversations. However, when attempting to monitor or influence conversations conducted as part of a meeting or a chat, the mood of the conversation is more important than the emotion. In normal conversation, emotions such as anger and sadness are unlikely to be explicitly expressed for some purposes, including avoidance of getting into an unexpected argument and offending others. Thus, when attempting to control or monitor the state of a conversation during a meeting or casual discussion, it is often more important to estimate the mood than the emotion. Some researchers have examined the role of mood, as distinguished from emotion, and one called diffuse emotional states that persist over a long period of time "mood" and are usually distinguished based on duration and intensity of expression. However, these differences are rarely quantified, and no specific durations are fixed. Accurate identification of the mood of a conversation is especially important for Japanese people who are engaged in collaborative and democratic decision making. To construct the teacher data for the model designed to estimate the conversational mood, we first selected representative adjective pairs that could describe the conversational mood. We utilized a system developed by Iiba et al. to estimate 21 affective scales of adjective pairs from input text. The 21 adjective pairs were clustered into 4 groups based on the output scales. The 4 adjective pairs to be annotated were representative of the 4 clusters. We expected these 4 adjective pairs (gloomy-happy, easy-serious, calm-aggressive, tidy-messy) to capture the mood of a conversation.Based on the four adjective pairs, we constructed a new training data set containing 60 hours of conversations in Japanese. In this study, the data obtained only by microphones are used for estimation of conversational mood. The data set was annotated by the four adjective scales to learn the mood of the conversations. We de-veloped a LSTM deep neural network model that could read the "conversational mood" in real time. Furthermore, in our proposed neural network model, the amount of laughter which is generally measured by capturing facial expression with camera is also estimated together with the conversational mood. Because laughter is considered to play an important role in creating a cheerful environment, it can be used to evaluate the conversational mood. The evaluation results are shown to present the validity of our model. This model is expected to be applied to a system that can influence or control the mood of conversations in some ways, including presentation of ambient music and aromas, depending on the purpose of the discussion, such as during a conference, chatting, or business meeting.
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Sharma, Ashish, Inna W. Lin, Adam S. Miner, Dave C. Atkins, and Tim Althoff. "Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approach (Extended Abstract)." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/747.

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Online peer-to-peer support platforms enable conversations between millions of people who seek and provide mental health support. If successful, web-based mental health conversations could improve access to treatment and reduce the global disease burden. Psychologists have repeatedly demonstrated that empathy, the ability to understand and feel the emotions and experiences of others, is a key component leading to positive outcomes in supportive conversations. However, recent studies have shown that highly empathic conversations are rare in online mental health platforms. In this paper, we work towards improving empathy in online mental health support conversations. We introduce a new task of empathic rewriting which aims to transform low-empathy conversational posts to higher empathy. Learning such transformations is challenging and requires a deep understanding of empathy while maintaining conversation quality through text fluency and specificity to the conversational context. Here we propose Partner, a deep reinforcement learning (RL) agent that learns to make sentence-level edits to posts in order to increase the expressed level of empathy while maintaining conversation quality. Our RL agent leverages a policy network, based on a transformer language model adapted from GPT-2, which performs the dual task of generating candidate empathic sentences and adding those sentences at appropriate positions. Through a combination of automatic and human evaluation, we demonstrate that Partner successfully generates more empathic, specific, and diverse responses and outperforms NLP methods from related tasks such as style transfer and empathic dialogue generation.
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Hanlon, Susannah, and Julie McLeod. "Human information behaviour in conversation: understanding the influence of informal conversation on learning in a political party." In ISIC: the Information Behaviour Conference. University of Borås, Borås, Sweden, 2020. http://dx.doi.org/10.47989/irisic2031.

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Introduction. This paper explores information behaviour in the underrepresented but increasingly important area of informal conversations and their influence on learning within political parties. The application of an extended model on information behaviour in conversation, which arose from the initial research analysis, enabled more granulated interpretation of results. This facilitated greater understanding, through the information behaviour lens, of informal conversations and how they contribute to learning. Method. Qualitative case-study of a political party. Analysis. Template analysis was used, followed by the application of the emergent extended model of human information behaviour in conversation. Results. Characteristics of informal conversation reflected the unique nature of the organisation. The extended model provided additional insights into context, information seeking and knowledge sharing during the conversations including motivations and affective factors, and outcomes from the conversations. Conclusions. A key reason for engaging in informal conversation was the need to strengthen capacity to influence. Self-efficacy was increased through mutual support and engaging in information behaviours. Application of the extended information behaviour model confirmed that learning occurred during informal conversations at individual and group level. Additional research is needed to test the model further with political parties and their members before extending it to wider applications.
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"Umeed: VR Game Using NLP Models and Latent Semantic Analysis for Conversation Therapy for People with Speech Disorders." In 4th International Conference on NLP Trends & Technologies. Academy & Industry Research Collaboration, 2023. http://dx.doi.org/10.5121/csit.2023.131408.

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UmeedVR aims to create a conversational therapy VR game using natural language processing for patients with Speech Disorders like Autism or Aphasia. This study developed 5 psychological task sets and 3 environments via Maya and Unity. The Topic-Modeling AI, employing 25 live participants' recordings and 980+ TwineAI datasets, generated initial VR grading with a coherence score averaging 6.98 themes in 5-minute conversations across scenarios, forming a foundation for enhancements. Employing latent semantic analysis (gensimcorpus Python) and Term-Frequency-Inverse Document-Frequency (TF-IDF), grammatical errors and user-specific improvements were addressed. Results were visualized via audio-visual plots, highlighting conversation topics based on occurrence and interpretability. UMEED enhances cognitive and intuitive skills, elevating average topics from 6.98 to 13.56 in a 5- minute conversation with a 143.12 coherence score. LSA achieved 98.39% accuracy, topic modeling 100%. Significantly, real-time grammatical correction integration in the game was realized.
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Nishida, Hikaru, Yumi Wakita, and Yotaro Iida. "The effect of topic-shift characteristics in daily conversation on identification of recognition errors." In 8th International Conference on Human Interaction and Emerging Technologies. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002757.

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To support senior and reclusive citizens’ smooth conversations, we have developed a conversation support system named “associative board”. it recognizes their conversation and provides several suitable topics for speakers when their conversation progress not so smooth. However. If there are too many recognition errors the system will not be able to present suitable words. The misrecognized words identification function is necessary for our associative board system. In this study, we clarify the problems with conventional misrecognized words identification methods for recognizing daily casual conversation. As results of evaluation, the conventional misrecognized words identification is effective for the conversations with predefined topics, however for casual conversations without predefined topic, the identification is difficult. The distribution of semantic similarity values among words for casual conversation are broader than that with predefined topics. When the semantic similarity values are under 0.3, despite the correct recognition utterances, that semantic similarity values of the recognition results are often lower than that of the misrecognition results. The 21.7% to all topics are that case. That means when the casual conversations in which the topic-shifting occurs frequently, the misrecognized words identification is difficult. The semantic similarity among recognized words should be calculated constantly, and when the semantic similarity values are high continuously or are low rarely, the identification method could be used. When the semantic similarity values are low continuously, the error words extraction and correction process should be stopped.
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Zhang, Ting, Zhuang Chen, Ming Zhong, and Tieyun Qian. "Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and Paraphrasing." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/699.

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Emotion recognition in conversation, which aims to predict the emotion for all utterances, has attracted considerable research attention in recent years. It is a challenging task since the recognition of the emotion in one utterance involves many complex factors, such as the conversational context, the speaker's background, and the subtle difference between emotion labels. In this paper, we propose a novel framework which mimics the thinking process when modeling these factors. Specifically, we first comprehend the conversational context with a history-oriented prompt to selectively gather information from predecessors of the target utterance. We then model the speaker's background with an experience-oriented prompt to retrieve the similar utterances from all conversations. We finally differentiate the subtle label semantics with a paraphrasing mechanism to elicit the intrinsic label related knowledge. We conducted extensive experiments on three benchmarks. The empirical results demonstrate the superiority of our proposed framework over the state-of-the-art baselines.
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Li, Jiangnan, Fandong Meng, Zheng Lin, Rui Liu, Peng Fu, Yanan Cao, Weiping Wang, and Jie Zhou. "Neutral Utterances are Also Causes: Enhancing Conversational Causal Emotion Entailment with Social Commonsense Knowledge." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/584.

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Conversational Causal Emotion Entailment aims to detect causal utterances for a non-neutral targeted utterance from a conversation. In this work, we build conversations as graphs to overcome implicit contextual modelling of the original entailment style. Following the previous work, we further introduce the emotion information into graphs. Emotion information can markedly promote the detection of causal utterances whose emotion is the same as the targeted utterance. However, it is still hard to detect causal utterances with different emotions, especially neutral ones. The reason is that models are limited in reasoning causal clues and passing them between utterances. To alleviate this problem, we introduce social commonsense knowledge (CSK) and propose a Knowledge Enhanced Conversation graph (KEC). KEC propagates the CSK between two utterances. As not all CSK is emotionally suitable for utterances, we therefore propose a sentiment-realized knowledge selecting strategy to filter CSK. To process KEC, we further construct the Knowledge Enhanced Directed Acyclic Graph networks. Experimental results show that our method outperforms baselines and infers more causes with different emotions from the targeted utterance.
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Chen, Yu, Lingfei Wu, and Mohammed J. Zaki. "GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/171.

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Conversational machine comprehension (MC) has proven significantly more challenging compared to traditional MC since it requires better utilization of conversation history. However, most existing approaches do not effectively capture conversation history and thus have trouble handling questions involving coreference or ellipsis. Moreover, when reasoning over passage text, most of them simply treat it as a word sequence without exploring rich semantic relationships among words. In this paper, we first propose a simple yet effective graph structure learning technique to dynamically construct a question and conversation history aware context graph at each conversation turn. Then we propose a novel Recurrent Graph Neural Network, and based on that, we introduce a flow mechanism to model the temporal dependencies in a sequence of context graphs. The proposed GraphFlow model can effectively capture conversational flow in a dialog, and shows competitive performance compared to existing state-of-the-art methods on CoQA, QuAC and DoQA benchmarks. In addition, visualization experiments show that our proposed model can offer good interpretability for the reasoning process.
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Reports on the topic "Conversation"

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Fronzak, Hannah. Community Conversation [Slides]. Office of Scientific and Technical Information (OSTI), July 2021. http://dx.doi.org/10.2172/1805709.

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Bishop, Arthur. Community Conversation 2023. Office of Scientific and Technical Information (OSTI), April 2023. http://dx.doi.org/10.2172/1969220.

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Hellstrom, G. RTP Payload for Text Conversation. RFC Editor, May 2000. http://dx.doi.org/10.17487/rfc2793.

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Hellstrom, G., and P. Jones. RTP Payload for Text Conversation. RFC Editor, June 2005. http://dx.doi.org/10.17487/rfc4103.

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David, Patty. AARP Research: A Conversation Starter About Age. AARP Research, May 2016. http://dx.doi.org/10.26419/res.00124.001.

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Quinn, Laura, and Ellen Van Velsor. Globally responsible leadership: A leading edge conversation. Center for Creative Leadership, 2008. http://dx.doi.org/10.35613/ccl.2008.2014.

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Traum, David R., and Elizabeth A. Hinkelman. Conversation Acts in Task-Oriented Spoken Dialogue. Fort Belvoir, VA: Defense Technical Information Center, June 1992. http://dx.doi.org/10.21236/ada256368.

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Davey, Lynn. Changing the public conversation about social problems. University of New Hampshire Libraries, 2008. http://dx.doi.org/10.34051/p/2020.50.

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Loignon, Andy, Diane Bergeron, and Karissa McKenna. Leadership as Conversation: A New Tool to Support Leadership Development. Center for Creative Leadership, 2024. http://dx.doi.org/10.35613/ccl.2024.2057.

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At the Center for Creative Leadership (CCL), our research suggests that leadership is a social process. That is, leadership is neither a matter of one’s inherent traits nor something that’s bestowed based on one’s job title. With leadership as a social process, one way to support leadership development is through conversational analysis, which captures the dialogue that unfolds among individuals as they strive towards shared outcomes. We developed a wearable technology system (i.e., HiFi, which is short for high-fidelity) and are pilot testing this system within one of CCL’s flagship programs – Leading for Organizational Impact (LOI). In the LOI program for executives and senior leaders, HiFi plays a significant role in helping leaders work more effectively across boundaries, increase their self-awareness, and understand how measured behaviors impact their perceived influence and effectiveness. Leaders want concrete actions they can take to improve their leadership skills. Using this innovative technology and evidence-based metrics, CCL provides behavioral insight into how leader conversations directly result in specific outcomes. For example, we can quantify how much a leader’s boundary spanning conversations contribute to the amount of influence they are afforded by their colleagues. Such insight can be a provocative tool that leaders use to enact behavioral change upon returning to their own organizations. In service of better leadership, conversations are a key lever for leader development.
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Washington, Sally. Building foresight capability - a curated conversation between jurisdiction. Australia and New Zealand School of Government, September 2022. http://dx.doi.org/10.54810/mlgx5385.

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Several ANZSOG jurisdictions are working to improve their foresight capability and to embed that capability within the work of government, making foresight as an essential element of policy design, policy capability and policy stewardship. An ANZSOG ‘curated conversation’ brought together senior officials from the Commonwealth, NSW and South Australia, to share lessons and approaches to improving foresight capability and to engage with the Singapore Government, considered a world leader in government foresight capability. This ‘conversation tracker’ captures the key themes of a broad-ranging discussion which have broad relevance to all jurisdictions looking to future-proof policy and build foresight into their work.
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