Towards Reproducible User Studies and Behavioral Experiments for Cartography With the stimsrv Framework

The modalities of communication are the sum of the expression dimension (linguistics) and the expressivity dimension (prosody), both being equally important in language communication. The expressivity dimension which comes first in the act of speech, is the basis on which phonemes, syllables, words, grammar and morphosyntax, i.e., the expression dimension of speech is superimposed. We will review evidence (1) revealing the importance of prosody in language acquisition and (2) showing that prosody triggers the involvement of specific brain areas dedicated to sentences and word-list processing. To support the first point, we will not only rely on experimental psychology studies conducted in newborns and young children but also on neuroimaging studies that have helped to validate these behavioral experiments. Then, neuroimaging data on adults will allow for concluding that the expressivity dimension of speech modulates both the right hemisphere prosodic areas and the left hemisphere network in charge of the expression dimension

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ViFin

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies ◽

10.1145/3448119 ◽

2021 ◽

Vol 5 (1) ◽

pp. 1-25

Author(s):

Wenqiang Chen ◽

Lin Chen ◽

Meiyi Ma ◽

Farshid Salemi Parizi ◽

Shwetak Patel ◽

...

Keyword(s):

Real Time ◽

Real World ◽

Wearable Devices ◽

User Studies ◽

Finger Movement ◽

Writing System ◽

Time System ◽

Real Time System ◽

Input Devices ◽

A New Technique

Wearable devices, such as smartwatches and head-mounted devices (HMD), demand new input devices for a natural, subtle, and easy-to-use way to input commands and text. In this paper, we propose and investigate ViFin, a new technique for input commands and text entry, which harness finger movement induced vibration to track continuous micro finger-level writing with a commodity smartwatch. Inspired by the recurrent neural aligner and transfer learning, ViFin recognizes continuous finger writing, works across different users, and achieves an accuracy of 90% and 91% for recognizing numbers and letters, respectively. We quantify our approach's accuracy through real-time system experiments in different arm positions, writing speeds, and smartwatch position displacements. Finally, a real-time writing system and two user studies on real-world tasks are implemented and assessed.

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The Upworthy Research Archive, a time series of 32,487 experiments in U.S. media

Scientific Data ◽

10.1038/s41597-021-00934-7 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

J. Nathan Matias ◽

Kevin Munger ◽

Marianne Aubin Le Quere ◽

Charles Ebersole

Keyword(s):

Data Mining ◽

Time Series ◽

Open Access ◽

Randomized Trial ◽

Digital Technology ◽

Behavioral Experiments ◽

Media Politics ◽

B Test ◽

Scientific Questions ◽

Advance Knowledge

AbstractThe pursuit of audience attention online has led organizations to conduct thousands of behavioral experiments each year in media, politics, activism, and digital technology. One pioneer of A/B tests was Upworthy.com, a U.S. media publisher that conducted a randomized trial for every article they published. Each experiment tested variations in a headline and image “package,” recording how many randomly-assigned viewers selected each variation. While none of these tests were designed to answer scientific questions, scientists can advance knowledge by meta-analyzing and data-mining the tens of thousands of experiments Upworthy conducted. This archive records the stimuli and outcome for every A/B test fielded by Upworthy between January 24, 2013 and April 30, 2015. In total, the archive includes 32,487 experiments, 150,817 experiment arms, and 538,272,878 participant assignments. The open access dataset is organized to support exploratory and confirmatory research, as well as meta-scientific research on ways that scientists make use of the archive.

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A Re-examination of Dichoptic Tone Mapping

ACM Transactions on Graphics ◽

10.1145/3443702 ◽

2021 ◽

Vol 40 (2) ◽

pp. 1-15

Author(s):

Minqi Wang ◽

Emily A. Cooper

Keyword(s):

Virtual Reality ◽

Visual System ◽

Contrast Enhancement ◽

User Studies ◽

Objective Measures ◽

Tone Mapping ◽

Photographic Technique ◽

Stereoscopic Displays ◽

Visual Detail

Dichoptic tone mapping methods aim to leverage stereoscopic displays to increase visual detail and contrast in images and videos. These methods, which have been called both binocular tone mapping and dichoptic contrast enhancement , selectively emphasize contrast differently in the two eyes’ views. The visual system integrates these contrast differences into a unified percept, which is theorized to contain more contrast overall than each eye’s view on its own. As stereoscopic displays become increasingly common for augmented and virtual reality (AR/VR), dichoptic tone mapping is an appealing technique for imaging pipelines. We sought to examine whether a standard photographic technique, exposure bracketing, could be modified to enhance contrast similarly to dichoptic tone mapping. While assessing the efficacy of this technique with user studies, we also re-evaluated existing dichoptic tone mapping methods. Across several user studies; however, we did not find evidence that either dichoptic tone mapping or dichoptic exposures consistently increased subjective image preferences. We also did not observe improvements in subjective or objective measures of detail visibility. We did find evidence that dichoptic methods enhanced subjective 3D impressions. Here, we present these results and evaluate the potential contributions and current limitations of dichoptic methods for applications in stereoscopic displays.

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A crowdsourced system for user studies in information extraction

International Journal of Knowledge Engineering and Soft Data Paradigms ◽

10.1504/ijkesdp.2017.089506 ◽

2017 ◽

Vol 6 (1) ◽

pp. 44

Author(s):

Zohreh Khojasteh Ghamari

Keyword(s):

Information Extraction ◽

User Studies

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Quantifying the Predictability of Visual Scanpaths Using Active Information Storage

Entropy ◽

10.3390/e23020167 ◽

2021 ◽

Vol 23 (2) ◽

pp. 167

Author(s):

Patricia Wollstadt ◽

Martina Hasenjäger ◽

Christiane B. Wiebel-Herboth

Keyword(s):

Information Storage ◽

Gaze Behavior ◽

Behavioral Experiments ◽

Human Machine Interaction ◽

Cognitive States ◽

Visual Scanpath ◽

Active Information Storage ◽

Temporal Horizon ◽

Machine Interaction ◽

Transition Entropy

Entropy-based measures are an important tool for studying human gaze behavior under various conditions. In particular, gaze transition entropy (GTE) is a popular method to quantify the predictability of a visual scanpath as the entropy of transitions between fixations and has been shown to correlate with changes in task demand or changes in observer state. Measuring scanpath predictability is thus a promising approach to identifying viewers’ cognitive states in behavioral experiments or gaze-based applications. However, GTE does not account for temporal dependencies beyond two consecutive fixations and may thus underestimate the actual predictability of the current fixation given past gaze behavior. Instead, we propose to quantify scanpath predictability by estimating the active information storage (AIS), which can account for dependencies spanning multiple fixations. AIS is calculated as the mutual information between a processes’ multivariate past state and its next value. It is thus able to measure how much information a sequence of past fixations provides about the next fixation, hence covering a longer temporal horizon. Applying the proposed approach, we were able to distinguish between induced observer states based on estimated AIS, providing first evidence that AIS may be used in the inference of user states to improve human–machine interaction.

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