Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App

Teki, Sundeep; Kumar, Sukhbinder; Griffiths, Timothy D.

doi:10.1371/journal.pone.0153916

Cited by 23 publications

(10 citation statements)

References 38 publications

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“…Nonetheless, consistent with the reported successful use of Smartphones in assessing cognitive abilities (e.g. [ 24 , 27 , 29 ]), physiological functions [ 41 , 42 ] and auditory processes [ 43 ], our results demonstrate the potential use of Smartphone applications for psychophysical measures of human visual performance. In particular, we suggest that Smartphones are a valid, convenient and cost-effective means of assessing the effect of everyday mood changes on the ability of individuals to perform visual searches (see also [ 44 ]).…”

Section: Discussionsupporting

confidence: 89%

The effect of mood state on visual search times for detecting a target in noise: An application of smartphone technology

et al. 2018

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The study of visual perception has largely been completed without regard to the influence that an individual’s emotional status may have on their performance in visual tasks. However, there is a growing body of evidence to suggest that mood may affect not only creative abilities and interpersonal skills but also the capacity to perform low-level cognitive tasks. Here, we sought to determine whether rudimentary visual search processes are similarly affected by emotion. Specifically, we examined whether an individual’s perceived happiness level affects their ability to detect a target in noise. To do so, we employed pop-out and serial visual search paradigms, implemented using a novel smartphone application that allowed search times and self-rated levels of happiness to be recorded throughout each twenty-four-hour period for two weeks. This experience sampling protocol circumvented the need to alter mood artificially with laboratory-based induction methods. Using our smartphone application, we were able to replicate the classic visual search findings, whereby pop-out search times remained largely unaffected by the number of distractors whereas serial search times increased with increasing number of distractors. While pop-out search times were unaffected by happiness level, serial search times with the maximum numbers of distractors (n = 30) were significantly faster for high happiness levels than low happiness levels (p = 0.02). Our results demonstrate the utility of smartphone applications in assessing ecologically valid measures of human visual performance. We discuss the significance of our findings for the assessment of basic visual functions using search time measures, and for our ability to search effectively for targets in real world settings.

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Section: Discussionsupporting

confidence: 89%

The effect of mood state on visual search times for detecting a target in noise: An application of smartphone technology

et al. 2018

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“…For example, some experiments require large numbers of participants (Kidd et al, 2007; McDermott et al, 2010; Hartshorne and Germine, 2015, Teki et al, 2016), and are much more efficiently conducted online, where hundreds of participants can be run per day. Experiments may also require recruiting participants from disparate cultural backgrounds (Curtis and Bharucha, 2009; Henrich et al, 2010) that are more readily recruited online than in person.…”

Section: Discussionmentioning

confidence: 99%

Headphone screening to facilitate web-based auditory experiments

Woods

Siegel²,

Traer³

et al. 2017

Atten Percept Psychophys

330

230

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Psychophysical experiments conducted remotely over the internet permit data collection from large numbers of participants, but sacrifice control over sound presentation, and therefore are not widely employed in hearing research. To help standardize online sound presentation, we introduce a brief psychophysical test for determining if online experiment participants are wearing headphones. Listeners judge which of three pure tones is quietest, with one of the tones presented 180° out of phase across the stereo channels. This task is intended to be easy over headphones but difficult over loudspeakers due to phase-cancellation. We validated the test in the lab by testing listeners known to be wearing headphones or listening over loudspeakers. The screening test was effective and efficient, discriminating between the two modes of listening with a small number of trials. When run online, a bimodal distribution of scores was obtained, suggesting that some participants performed the task over loudspeakers despite instructions to use headphones. The ability to detect and screen out these participants mitigates concerns over sound quality for online experiments, a first step toward opening auditory perceptual research to the possibilities afforded by crowdsourcing.

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“…In earlier work, we used a stimulus design where the figure appeared for a brief duration (ranging from 50 to 350 ms) amidst an ongoing random chord sequence ( Teki et al 2011 , 2013 , 2016 ). For the present study, the stimulus was modified such that the figure was introduced exactly midway during the stimulus and remained present until offset as shown in Figure 1 .…”

Section: Methodsmentioning

confidence: 99%

Neural Correlates of Auditory Figure-Ground Segregation Based on Temporal Coherence

et al. 2016

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To make sense of natural acoustic environments, listeners must parse complex mixtures of sounds that vary in frequency, space, and time. Emerging work suggests that, in addition to the well-studied spectral cues for segregation, sensitivity to temporal coherence—the coincidence of sound elements in and across time—is also critical for the perceptual organization of acoustic scenes. Here, we examine pre-attentive, stimulus-driven neural processes underlying auditory figure-ground segregation using stimuli that capture the challenges of listening in complex scenes where segregation cannot be achieved based on spectral cues alone. Signals (“stochastic figure-ground”: SFG) comprised a sequence of brief broadband chords containing random pure tone components that vary from 1 chord to another. Occasional tone repetitions across chords are perceived as “figures” popping out of a stochastic “ground.” Magnetoencephalography (MEG) measurement in naïve, distracted, human subjects revealed robust evoked responses, commencing from about 150 ms after figure onset that reflect the emergence of the “figure” from the randomly varying “ground.” Neural sources underlying this bottom-up driven figure-ground segregation were localized to planum temporale, and the intraparietal sulcus, demonstrating that this area, outside the “classic” auditory system, is also involved in the early stages of auditory scene analysis.”

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Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App

Cited by 23 publications

References 38 publications

The effect of mood state on visual search times for detecting a target in noise: An application of smartphone technology

The effect of mood state on visual search times for detecting a target in noise: An application of smartphone technology

Headphone screening to facilitate web-based auditory experiments

Neural Correlates of Auditory Figure-Ground Segregation Based on Temporal Coherence

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