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Combining Character and Conversational Types in Strategic Choice

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Combining Character and Conversational Types in Strategic Choice Different Games in Dialogue: Combining character and conversational types in strategic choice Alafate Abulmiti Universite´ de Paris, CNRS Laboratoire de Linguistique Formelle [email protected] Abstract We seek to develop an approach to strategic choice applicable to the general case of dialogical In this paper, we show that investigating the in- interaction, where termination is an important con- teraction of conversational type (often known sideration and where assessment is internal to the as language game or speech genre) with the character types of the interlocutors is worth- participants. Strategic choice is modelled by com- while. We present a method of calculating the bining structure from conversational types with psy- decision making process for selecting dialogue chological and cognitive notions associated with moves that combines character type and con- the players. versational type. We also present a mathemat- Character type as a relatively independent factor ical model that illustrate these factors’ interac- abstracted out of the conversational type is impor- tions in a quantitative way. tant for dialogue. Although there is some analy- 1 Introduction sis concerning both character effects and conversa- tional types in the dialogue, combining them and Wittgenstein(1953); Bakhtin(2010) introduced analyzing their interactions in a quantitative way language games/speech genres as notions tying di- has not, to our knowledge, been carried out before. versity of linguistic behaviors to activity. Build- The purposes of this paper is, hence, to combine ing on this, and insights of pragmaticists such as character type effect and conversational type anal- Hymes(1974); Allwood(2000), and earlier work ysis to yield a method that could help to analyse in AI by (Allen and Perrault, 1980; Cohen and strategic choice in dialogue. Perrault, 1979) Larsson(2002); Ginzburg(2012); Wong and Ginzburg(2018) showed how to asso- 2 Background ciate global structure with conversations in a way The starting point of (Asher et al., 2017) is the that captures the range of possible topics and id- framework of Banach-Mazurckiewicz games. They iosyncratic moves. (Larsson, 2002) is also the basis modify this framework to make it more amenable for an approach to building spoken dialogue sys- to analyzing certain kinds of NL dialogue, the emer- tems (SDS) which is essentially domain general, gent framework being BM messaging games. Asher offers a fine-grained treatment of grounding inter- et al.(2017) argued that each dialogue potentially action, and which was extended to clarification continues indefinitely and has a winner adjudged interaction in (Purver, 2004). by a third party jury. This is useful for modelling This body of work does not address, however political discourse between rival groups or individ- the issue of strategic choice in conversation, which ual contenders in the public domain. But clearly is the core issue underlying work in Game Theory. this sort of conception is not appropriate for a vari- Asher et al.(2017) used game theoretic tools to ety, arguably most types of dialogue.1 These have develop a theory of strategic choice for dialogue. beginnings (InitState) and a variety of distinct Although there are a variety of interesting insights terminations (F inState)(Wong, 2018), and there captured in this approach, it is based on two as- sumptions that apply only to a restricted class of 1Strictly speaking, Asher et al.(2017) allowed also for language games—games continue indefinitely and finite games, by allowing for games to consist of a special move from a certain point onwards, but this would seem to there exists a jury that assigns winning conditions either defeat the purpose of assuming potential extendibility to participants. or to be purely formal. is no ‘external jury’ in most cases. aspects of human personality. The Big Five Per- Burnett(2019) developed a formal model called sonality (OCEAN) can be assessed by the NEO-PI- social meaning games which explains how social R(Costa Jr and McCrae, 2008). The traits can be variants affect the linguistic style of dialogue par- described as follows: ticipants. And conversely, how the speaker’s in- trinsic linguistic style affects dialogue moves. Pen- • Openness: the ability to be imaginative, aes- nebaker and King(1999) shows that linguistic style thetic, emotional, creative, intelligent, etc. is an independent and meaningful way of explor- ing personality. There is evidence that people’s • Conscientiousness: displays characteristics personality traits influence their use of language. such as competence, fairness, organization, For instance, extroverted individuals are able to de- due diligence, achievement, self-discipline, ceive others more easily, while neurotic individuals caution, restraint, etc. are less likely to be deceived (Riggio et al., 1988). The charisma of a speaker has been shown to be • Extroversion: exhibits qualities such as en- closely related to an extroverted character (Bono thusiasm, sociability, decisiveness, activity, and Judge, 2004). There is also a strong relation adventure, optimism, etc. between extroversion and conscientiousness and positive influences, as well as between neuroticism • Agreeableness: the qualities of trust, altru- and dissent and various negative influences(Watson ism, straightforwardness, compliance, humil- and Clark, 1992). Thus, an individual’s personality ity, empathy, etc. does affect decision-making process in dialogue. Cooperation in dialogue is a widespread phe- • Neuroticism: difficulty balancing emotional nomenon, and Allwood et al.(2000) identified traits such as anxiety, hostility, repression, four features of cooperation: cognitive consider- self-awareness, impulsivity, vulnerability, etc. ation, joint purpose, ethical consideration and trust. When engaging in a collaborative dialogue, where Goldberg(1992) gave a pertinent method to the interlocutor decides his next move based on quantify character types in terms of 5 dimensional the intentions of the other and a variety of infor- vector [o; c; e; a; n]. We define χ for the self char- mation deriving from the context of the dialogue, s acter type scale vector and χ represents other char- it seems that character has a broad influence on o acter type scale vector. the course of the dialogue. Thus, it seems natural that a dialogue participant (DP) should also take In addition, with the development of machine into account the other’s character traits in order to learning and deep learning methods within NLP, choose the appropriate move. a variety of approaches have been implemented In the next section, we will explain the method for automatic recognition of personality in con- we propose of combining character type effects and versation and text (Mairesse et al., 2007). Jiang conversational type. et al.(2019) used attentive network and contex- tual embeddings to detect personality traits from 3 Methodology monologues and multiparty dialogues. Given a text(or utterance), one can calculate the character In this section, we wish to explore the interaction type scale vector of this sentence with a robust pre- between character type and conversational type, by diction model. We define ci as ith dialogue move considering how given a possible range of moves, vector prediction. a quantitative analysis can be provided for move We note that by calculating the similarity be- selection. tween the χ and ci, we obtain the extent to which a given dialogue move can fit either the self character 3.1 Character Type type or the other character type. Note that χs is Researchers have developed a relatively unani- a dialogue interlocutor’s intrinsic property which mous consensus on personality description pat- does not show great change during conversation, terns, proposing the Big Five model of person- but considering one’s imperfect information situa- ality(Goldberg, 1992). Within this model there tion, χo will change once new evidence arises and are five traits that can be used to capture many can be modified by applying Bayes’ rule. 3.2 Conversational Type sifies the interaction they are in, as for instance in Pennebaker and King(1999) also indicated that (1): linguistic style gets influenced by the situation in (1) (Context: A is being interviewed by B) which the interlocutor find themselves. Wong and A: Hi B: Hi . B (1): have you seen Ginzburg(2018) provided a topological perspective Blackklansman yet? A (2): Wait— is this on the space of conversational types based on the an informal chat or a formal interview? B: distribution of Non-Sentential Utterances (NSU) A bit of both. (Example (54) from (Wong, within each type. Wong(2018) developed a model 2018). of a conversational type couched in TTR (Cooper, 2005). On this view, a conversational type is a Thus, the DP has an opaque or uncertain ”guess” 4-tuple fConvRules, InitState, F inState, Gg, as to the conversational type and this also influ- here ConvRules represents a set of conversational ences the decision-making process. Following rules, transition rules between different dialogue probabilistic TTR theory (Cooper et al., 2014), states (dialogue gameboards) of type DGBT ype we assume that the DP has a probabilistic con- (Ginzburg, 2012), InitState and F inState are versational type in the private part of information the initial and final DGB states. state and this can be updated during dialogue by DGBT ype 7! Bayesian inference. We model the information 2 3 spkr: Ind state as follows: 6 7 InformationState = 6addr: Ind 7 6 7 2 2 " #33 6utt-time: Time 7 Self: Vector 6 7 6 CharacterType: 7 6c-utt: adressing(spkr, addr, utt-time) 7 6 6 Other: Vector 77 6 7 6 6 77 6 7 6 6 77 6FACTS: set(Proposition) 7 6 6Goals: Set(Prop) 77 6 7 6private =6 77 6Pending: list(Locutionary Proposition)7 6 6Tmp: private 77 6 7 6 6 77 6Moves: list(Locutionary Proposition) 7 6 6 77 4 5 6 6ConvType : ConvType 77 6 4 57 QUD: poset(Question) 6 Conv-prob : [0, 1] 7 G is the grammar which serves for the different 4 5 dgb :DGBType conversational language use.
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