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30 results for “Sonification”
Papers on Google Scholar using "sonification, auditory display, audification, sonify" as search terms
<p>Data set from a Google Scholar search in January 2023 on the terms "sonification, auditory display, audification, sonify" and added abstracts from various online ressources and keywords (automatically extracted from the abstracts only), containing:</p> <ul> <li>their title,</li> <li>a website/URL (as referenced by Google scholar),</li> <li>author(s),</li> <li>publisher information,</li> <li>their google rank in our search,</li> <li>publication year,</li> <li>the number of citations;</li> <li>paper abstracts;</li> <li>keywords generated from abstracts.</li> </ul>
Accessible Oceans: Data Sonification Wrapper Earcons
<p>Original, earcon sounds to play before and after a data sonification. These auditory icons ensure there is a clear notification of the start and stop of the sonifications so that the learner knows when to start fully listening and then knows when the sonification is over.</p> <p>A semi-structured interview with two BLV teachers at the Perkins School for the Blind offered several ideas for helpful tactics in how to use sound to explain the principles of graphs. Sounds wrapping data sonifications was one best practice that emerged from the interview. We created original earcons for our project to serve this specific function.</p>
Gallup Data Sonification Experiment
<p>Sound stimuli designed for the experiment.</p> <p>Q11.wav - Question 1 Sound 1, Sound of the engaged workers at 31% </p> <p>Q12.wav - Question 1 Sound 2, Sound of the actively disengaged workers at 22% </p> <p>Q13.wav - Question 1 Sound 3, Sound of the engaged workers at 10% </p> <p>Q14.wav - Question 1 Sound 4, Sound of the not engaged workers at 74% </p> <p>Q15.wav - Question 1 Sound 5, Sound of the actively disengaged workers at 10% </p> <p>Q21.wav - Question 2 Sound 1, Sound of the engaged workers at 15%, not engaged workers at 70% and actively disengaged workers at 15%</p> <p> Q22.wav - Question 2 Sound 2, Sound of the engaged workers at 50%, not engaged workers at 35% and actively disengaged workers at 15%</p> <p> Q23.wav - Question 2 Sound 3, Sound of the engaged workers at 15%, not engaged workers at 35% and actively disengaged workers at 50%</p> <p> Q31.wav - Question 3 Sound 1, representing U.S./Canada, Sound of the engaged workers at 31%, not engaged workers at 52% and actively disengaged workers at 17%</p> <p> Q32.wav - Question 3 Sound 2, representing East Asia, Sound of the engaged workers at 6%, not engaged workers at 74% and actively disengaged workers at 20%</p> <p> Q33.wav - Question 3 Sound 3, representing Sub-Saharan Africa, Sound of the engaged workers at 17%, not engaged workers at 65% and actively disengaged workers at 18%</p> <p> Q34.wav - Question 3 Sound 4, representing Western Europe, Sound of the engaged workers at 10%, not engaged workers at 71% and actively disengaged workers at 19%</p> <p> Q35.wav - Question 3 Sound 5, representing Latin America, Sound of the engaged workers at 27%, not engaged workers at 59% and actively disengaged workers at 14%</p> <p> Q36.wav - Question 3 Sound 6, representing Middle East/North Africa, Sound of the engaged workers at 14%, not engaged workers at 64% and actively disengaged workers at 22%</p>
Data for The Design and Formalization of an Embodied Soundscape Sonification Framework
<p>This repository contains evaluation data ane experimental stimuli for the paper :The Design and Formalization of an Embodied Soundscape Sonification Framework.</p>
Dataset of RQA-based measures of a minimalist perceptual task using sonification
<p>Dataset of RQA-based measures of a minimal perceptual task using sonification</p>
Sonification of data from Deep Sea Hunter Demonstrator (KM3NeT)
<p>The video present an image sonification of data obtained from the Deep Sea Hunter demonstrator. The development was grant by the European Union, under the project REINFORCE. The data was obtained during this collaboration from researchers from the KiloMeter Cube Neutrino Telescope (KM3NeT).</p> <p>"The REINFORCE project has received funding from the European Union’s Horizon 2020 project call H2020-SwafS-2018-2020 funded project Grant Agreement no. 872859"</p> <p> </p> <p>For more information visit:</p> <p>www.reinforceeu.eu/</p> <p>www.zooniverse.org/projects/reinforce/deep-sea-explorers</p>
Sonification of Glitches (GW-EGO)
<p>The videos present an image sonification of Glitches, one Blip and the other scattered light, both are different type of Glitches. The development was grant by the European Union, under the project REINFORCE. The data was obtained during this collaboration from the European Gravitational Observatory (EGO).</p> <p>"The REINFORCE project has received funding from the European Union’s Horizon 2020 project call H2020-SwafS-2018-2020 funded project Grant Agreement no. 872859"</p> <p> </p> <p>For more information visit:</p> <p>www.reinforceeu.eu/</p> <p>www.zooniverse.org/projects/reinforce/gwitchhunters</p>
Muongraphy sonification (IP2I)
<p>The video present the sonification of Muongraphy data, with and without the existence of a muon. The development was grant by the European Union, under the project REINFORCE. The data was obtained during this collaboration from the Institute of Physics of the 2 Infinities of Lyon (IP2I).</p> <p>"The REINFORCE project has received funding from the European Union’s Horizon 2020 project call H2020-SwafS-2018-2020 funded project Grant Agreement no. 872859"</p> <p> </p> <p>For more information visit:</p> <p>www.reinforceeu.eu/</p> <p>www.zooniverse.org/projects/reinforce/cosmic-muon-images</p>
Sonification of the human meniscus
<p>AudioFiles478. Sonification of 478 image files from microCT scans of human meniscus sample VOI(4) for which the images were compressed to 64 x 64 pixels. </p> <p>AudioFiles7648. Sonification of 7648 image files from microCT scan of human meniscus sample VOI(4) for which the full resolution of the images of 256 x 256 pixels is retained.</p> <p>Materials and methods described in: </p> <p>"The applicability of transperceptual and deep learning approaches to the study and mimicry of complex cartilaginous tissues". Waghorne J., Howard C., Hu H., Pang J., Peveler W.J., Harris L., Barrera O.</p> <p>Accepted in Frontiers in Materials-Computational Materials Science and available here: DOI: 10.3389/fmats.2023.1092647</p>
Example sonifications from the Astronify open-source Python package.
<p>The file named "10_galexFlare.wav" is a sonification of a stellar flare observed by the GALEX space telescope. This sonification uses a linear stretch on the pitch range 100-10,000 Hz, with a note duration of 0.8 seconds and 0.04 seconds between notes. The file named "1_kepler12b.wav" is a sonification of a transiting exoplanet observed by the Kepler space telescope. This sonification uses a linear stretch on the pitch range 100-10,000 Hz, with a note duration of 0.5 seconds and 0.01 seconds between notes.</p>
A Universe of Sound: Processing NASA Data into Sonifications to Explore Participant Response
<p>Files containing additional data for the first and second open-ended response questions of the survey discussed in Section 3.3 of the paper "A Universe of Sound: Processing NASA Data into Sonifications to Explore Participant Response" and text descriptions of the associated sonifications of three astronomical objects (the Galactic Center, Cassiopeia A, and the Chandra Deep Field South).</p>
The Air Listening Station: Bridging the gap between Sound Art and Sonification - Sonification examples
<p><strong>Example audio files:</strong></p> <p>1) aesthetic_direction_01.mp3 --> Initial aesthetic direction/proof of concept created using 1 hour of PM_10 and PM_2.5 data rendered at a 10:1 ratio (i.e. 60 minutes of air quality data results in 6 minutes of audio). Created using the Ultimate Grainer module of Ajax Sound Studio’s Cecilia 5 audio signal processing environment.</p> <p>2) sample sonification - original - good AQ - 5x bad AQ.mp3 --> contains several example outputs created using the sonification instrument created in Supercollider presented during the <a href="https://radioart.zone/sunday-28-august">radio art zone broadcast on August 28, 2022</a></p> <ul> <li>[0:00] - original field recording before processing</li> <li>[0:30] - example of "good" air quality data</li> <li>[1:02] - example of "bad" air quality data #1</li> <li>[2:10] - example of "bad" air quality data #2</li> <li>[2:45] - example of "bad" air quality data #3</li> <li>[3:08] - example of "bad" air quality data #4</li> <li>[3:38] - example of "bad" air quality data #5</li> </ul>
Supplementary material for "Sounding Obstacles for Social Distance Sonification".
<p>Supplementary material for the paper "Sounding Obstacles for social distance Sonification": Three videos (FmodI, FmodD, and NoFS) demonstrating three experimental conditions and 16 simulated videos (DD 01 - SS 06) presenting scenarios used in the experiment.</p>
Sonification of the atmospheric carbon record: 1988–1992 and 2014–2019
<p><span>These two pieces are part of a collection of sound compositions called <em>Timescales</em>, which sonifies datasets spanning different time scales of the atmospheric carbon record. Sonification is analogous to visualization. In visualizations, data is mapped to an image; in sonification data is mapped to sound. <em>In Situ 1988</em> and <em>In Situ 2014</em> both sonify five years of atmospheric carbon data from the Mauna Loa Observatory, commonly known as the Keeling Curve. The pieces present the carbon record at weekly, monthly, and yearly timescales with a musical scale and translate historical time to musical time. Unlike standard graphical presentations of data, these sound compositions allow the listener to hear the data as physical resonance over time. </span></p>
Sonification of the atmospheric carbon record over the past 800,000 years
<p><span>This piece is part of a collection of sound compositions called <em>Timescales</em>, which sonifies datasets spanning different time scales of the atmospheric carbon record. Glaciations is a musical sonification of atmospheric carbon dioxide inferred from ice cores, from 800,000 years ago to the present. This scale encompasses the small shifts in earth's orbit which drove the rise and fall of eight successive ice ages and alternating warm periods. The intention behind the compositional choices in this composition is to evoke a sense of vastness and wonder, and to create a sonic landscape of planetary motion and deep time.</span></p>
Sonification of Chemotactic Waves of Bacteria - Video Dataset
<p>Sonifications of videos of fluorescent <em>E. coli</em> bacteria migrating towards or away from an agar interface with a chemical of interest. </p> <p>Collated for The 28th International Conference on Auditory Display (ICAD 2023) June 26 – July 1 2023, Norrköping, Sweden</p>
THE SONIFICATION OF GENETIC VARIABILITY AS A COMMUNICATION TOOL
<p>An innovative approach that uses sonification to communicate the comparison of individuals and effectively convey their genetic variability. This study culminated in the development of two distinct sonification methods. The methods adopted were audification (Sonification A) and parameter (or musical) mapping sonifications (Sonification B). </p>
Sonification of the atmospheric carbon record: 1988–1992 and 2014–2019
Open the record for dataset details and reuse information.
Sonification of the atmospheric carbon record over the past 800,000 years
Open the record for dataset details and reuse information.
Sonic Kayak environmental data sonification survey results
<p>This data set is part of the Sonic Kayak project https://fo.am/activities/kayaks/</p> <p>A survey was performed online in June 2020, to gather people's opinions on different environmental data sonification approaches, and test whether people could tell what was happening in the data just from the sounds they heard. This was designed to inform our choices of which sonifications to use, rather than as a scientific study of sonification approaches. A total of 49 people completed the survey. The data presented is in its raw form.</p>
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