This article presents an applied discussion of the possibility of integrating conversation analysis (CA) methodology into that of machine learning. The aim is to improve the detection of that which resembles disengagement in the interaction between a robot and a human. We offer a novel analytical assemblage at the heart of the two disciplines, and namely on the level of the annotation schemes provided by conversation analysis transcription methods. First, we demonstrate that the need for a stable structure in establishing (...) an interaction scenario and in designing robot behaviours does not prevent the emergence of ordinariness or creativity among the participants engaged in this interaction. Secondly, based on an actual case, we emphasize the possibility of systematicness in CA transcription to support the choice (a) of the categories targeted by prediction methods and defined by the annotation scheme, and (b) of the verbal and non-verbal features used to create prediction models. (shrink)

Dans cet article j’envisage la problématique du « discours rattrapé par la situation » non comme un fait rare, mais comme une propriété générique de tout événement social : l’organisation du discours en interaction (la conversation, une conférence, une performance poétique) suppose un contexte qu’il contribue réflexivement à structurer. Je souhaite le montrer en ayant recours à l’analyse de situations a priori extra-ordinaires, où des aspects troublants, angoissants, morbides font enfler des phénomènes humains structurant des pratiques sociales en général. Par (...) là, je m’appuierai sur une perspective endogène du contexte, et j’introduirai une discussion sur l’approche interactioniste vis-à-vis de notions telles que l’information, ou la normalité. (shrink)

This article presents an applied discussion of the possibility of integrating conversation analysis (CA) methodology into that of machine learning. The aim is to improve the detection of that which resembles disengagement in the interaction between a robot and a human. We offer a novel analytical assemblage at the heart of the two disciplines, and namely on the level of the annotation schemes provided by conversation analysis transcription methods. First, we demonstrate that the need for a stable structure in establishing (...) an interaction scenario and in designing robot behaviours does not prevent the emergence of ordinariness or creativity among the participants engaged in this interaction. Secondly, based on an actual case, we emphasize the possibility of systematicness in CA transcription to support the choice (a) of the categories targeted by prediction methods and defined by the annotation scheme, and (b) of the verbal and non-verbal features used to create prediction models. (shrink)