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Transcript-based computer animation of movement: Evaluating a new tool for nonverbal behavior research

A new approach for the use of computer animation in experimental nonverbal research is intro- duced. The method was evaluated in a pilot study comparing video recordings of movement in dyadic interactions with computer animations based on transcripts of the behavior, to determine whether sim- ilar impression effects could be obtained. At the core of our development is a software tool allowing for the conversion of so-called position time-series protocols of movement into animation scripts for a professional computer animation platform. Our software combines computer-assisted movement transcription and editing with state-of-the-art 3-D animation technology. We present empirical evidence indicating remarkable overall correspondence between video recordings and computer animations. Due to the lack of facial activity in the computer animations, a decline in visual attention for the face area could be observed, which did not, however, affect the impression ratings.

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Adopting an eyetracking paradigm, we investigated the role of H*L, L*HL, L*H, H*LH, and deaccentuation at the intonational phrase-final position in online processing of information status in British English in natural speech. The role of H*L, L*H and deaccentuation was also examined in diphone- synthetic speech. It was found that H*L and L*HL create a strong bias to- wards newness, whereas L*H, like deaccentuation, creates a strong bias to- wards givenness. In synthetic speech, the same effect was found for H*L, L*H and deaccentuation, but it was delayed. The delay may not be caused entirely by the difference in the segmental quality between synthetic and natural speech. The pitch accent H*LH, however, appears to bias participants’ interpretation to the target word, independent of its information status. This finding was ex- plained in the light of the effect of durational information at the segmental level on word recognition.

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Improving Human Interaction Research through Ecological Grounding

In psychology, we tend to follow the general logic of falsificationism: we separate the ‘context of discovery’ (how we come up with theories) from the ‘context of justification’ (how we test them). However, when studying human interaction, separating these contexts can lead to theories with low ecological validity that do not generalize well to life outside the lab. We propose borrowing research procedures from well-established inductive methodologies in interaction research during the process of discovering new regularities and analyzing natural data without being led by theory. We introduce research procedures including the use of naturalistic study settings, analytic transcription, collections of cases, and data analysis sessions, and illustrate these with examples from a successful cross-disciplinary study. We argue that if these procedures are used systematically and transparently throughout a research cycle, they will lead to more robust and ecologically valid theories about interaction within psychology and, with some adaptation, can enhance the reproducibility of research across many other areas of psychological science.

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Multimodal Interaction
Collect high quality video recordings of spontaneous, naturally- occurring interaction for transcription
To acquire a corpus of video data, for investigating the underlying structure(s) of interaction cross-linguistically and cross-culturally.

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The goal of this project is to gather cross cultural information on listeners’ feedback behavior during conversation. Listeners in a conversation usually provide short signals that indicate to the speaker that they are still “with the speaker”. These signals could be verbal (like for instance “mm hm” in English or “hm hm” in Dutch) or nonverbal (visual), like nodding. Often, these signals are produced in overlap with the speaker’s vocalization. If listeners do not produce these signals, speakers often invite them explicitly (e.g. “are you still there?” in a telephone conversation). Our goal is to investigate what kind of signals are used by listeners of different languages to signal “recipiency” to the speaker.

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The Human Interaction Laboratory Data session will meet on Friday, October 11th, 2019 in unit 2614, 200 Boston Ave. Medford, MA 02155.

If you don’t know what a data session is, you can read Saul’s description of learning about Conversation Analytic data sessions, or have a look at this resource from Arizona State University that discusses language and social interaction data analysis sessions from a variety of methodological/disciplinary perspectives: https://www.learninghowtolookandlisten.com.

See our full list of data sessions on our events page.

RSVP: julia.mertens@tufts.edu

Data:  Raea Rasmussen, a PhD student in the Psychology department at Tufts University, will present data on comfort discussing race in cross-race interactions.

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If you’d like information about upcoming data sessions and announcements at the Human Interaction Lab, please subscribe to our mailing list.

The Human Interaction Laboratory Data session will meet on Friday, September 13th 2019 at 200 Boston Ave. Medford, MA 02155. Exact room location is TBD.

If you don’t know what a data session is, you can read Saul’s description of learning about Conversation Analytic data sessions, or have a look at this resource from Arizona State University that discusses language and social interaction data analysis sessions from a variety of methodological/disciplinary perspectives: https://www.learninghowtolookandlisten.com.

See our full list of data sessions on our events page.

RSVP: julia.mertens@tufts.edu

Data: Bryanna Hebenstreit (Ph.D. Candidate at the University at Albany, SUNY) will provide video data of an instance where a participant becomes familiar with a floorboard cutting tool on a home refurbishment site. This data provides a look at how participants arrange themselves in relationship to the tool, how participants project their usage of the tool, how other participants are brought into the interaction, and how ‘experienced’ onlookers may anticipate by the embodied conduct of a participant potential consequences of that arrangement and exclaim or otherwise attempt to avert undesirable consequences. Data is in American English.

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If you’d like information about upcoming data sessions and announcements at the Human Interaction Lab, please subscribe to our mailing list.

The Human Interaction Laboratory Data session will meet on Thursday, March 28th 2019 in unit 2614, 200 Boston Ave. Medford, MA 02155.

If you don’t know what a data session is, you can read Saul’s description of learning about Conversation Analytic data sessions, or have a look at this resource from Arizona State University that discusses language and social interaction data analysis sessions from a variety of methodological/disciplinary perspectives: https://www.learninghowtolookandlisten.com.

See our full list of data sessions on our events page.

RSVP: julia.mertens@tufts.edu

Data: Dr. Kristen Bottema-Beutel and Dr. Gabrielle Oliviera from Boston College will be presenting data on Question-Response-Evaluation (QRE) sequences in the home interactions of a bilingual child with Autism Spectrum Disorder. We will focus on QRE sequences within interactions between a 5-year old bilingual child with ASD and his parents. In these sequences, the adult poses known-answer questions, the child responds, and the adult evaluates the response. QRE sequences are primarily structured by the questioner (i.e., the parents in our context), so we will focus on the interactive work done by parents to initiate, maintain, and close these sequences. 

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If you’d like information about upcoming data sessions and announcements at the Human Interaction Lab, please subscribe to our mailing list.