I gave this keynote at the first European conversation analysis (ECCA 2020), which, due to C-19, had to be delivered as a video instead of a stand-up.

I tried to make a mix between a movie essay and a work research presentation in progress, so it didn’t always work to put references on each slide. I added them below with links to the used data where available.

Abstract

Sacks ‘(1963) The first published document on a’ sociological description ‘uses the metaphor of a mysterious’ speaking and ‘rush’ machine, where researchers from different disciplines come up with incompatible and contradictory descriptions of its functionality. We can soon find ourselves in a situation similar to what the one bag describes as the AI ​​continues to perfect the social sciences, and CA begins to meet the AI ​​or as a research object, as a research tool, or more likely as a widespread feature of both.

There is now a strong industry in ‘AI of conversation’ and AI-based tools that claim to imitate or analyze discussion, but both the study and the use of AI within CA are still unusual. While growing literature is using CA to study social robotics, voice interfaces, and conversation user experience (Pelikan & Broth, 2016; Porcheron et al., 2018), a few conversation analysts even use digital tools, think and see the statistical and computing methods. Similarly, researchers and developers of AI of conversation rarely quote CA research and have recently become interested only in CA as a possible solution to tough problems in natural language processing (NLP). This situation presents an opportunity for mutual commitment between the AI ​​of conversation and CA (Housley et al., 2019). To prepare a debate on this issue, I will present three projects that connect AI and CA very differently and discuss the implications and possibilities for combined research programs.

The first project uses a unique case analysis series to explore recordings containing AI of successfully advanced conversation making appointments on the phone with call-call. The second review of debates on the use of automatic speech recognition for CA transcript (Moore, 2015) in light of significant recent advances in speech to AI-based test, and includes a direct demo of ‘GailBot’, a Jeffersonian automated transcript system. The third project both uses and AI studies in a CA context applied. When using video analysis, she asks how a disabled man and his care worker interact while using AI-based voice interfaces and a ‘home automation’ system designed co-designed as part of a domestic resurrection routine, food, and personal care. The data is drawn from Corpus of ~ 500 hours of video data recorded by participants using a voice-controlled ‘smart security camera’ system.

These three examples of potential interpretations and potential uses of ‘talking’ CAs and make AI provide debate material on how CA research programs can concept AI, and use it or connect it to CA in a mutually informative manner.

Videos (in the appearance order)

Senster– (2007, March 29).

What ball ai– (2011, September 25).

Keynote (Google I / O ’18)– (2018, May 9).

Online data

Language data consortium. (2013). Cabank Callhome Corpus English [Data set]- Talkbank.

Jefferson, G. (2007). English Cabank Jefferson NB Corpus [Data set]- Talkbank.

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