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name="abstracts" type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2407.12260">arXiv:2407.12260</a> <span> [<a href="https://arxiv.org/pdf/2407.12260">pdf</a>, <a href="https://arxiv.org/format/2407.12260">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> HuBar: A Visual Analytics Tool to Explore Human Behaviour based on fNIRS in AR guidance systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Castelo%2C+S">Sonia Castelo</a>, <a href="/search/cs?searchtype=author&query=Rulff%2C+J">Joao Rulff</a>, <a href="/search/cs?searchtype=author&query=Solunke%2C+P">Parikshit Solunke</a>, <a href="/search/cs?searchtype=author&query=McGowan%2C+E">Erin McGowan</a>, <a href="/search/cs?searchtype=author&query=Wu%2C+G">Guande Wu</a>, <a href="/search/cs?searchtype=author&query=Roman%2C+I">Iran Roman</a>, <a href="/search/cs?searchtype=author&query=Lopez%2C+R">Roque Lopez</a>, <a href="/search/cs?searchtype=author&query=Steers%2C+B">Bea Steers</a>, <a href="/search/cs?searchtype=author&query=Sun%2C+Q">Qi Sun</a>, <a href="/search/cs?searchtype=author&query=Bello%2C+J">Juan Bello</a>, <a href="/search/cs?searchtype=author&query=Feest%2C+B">Bradley Feest</a>, <a href="/search/cs?searchtype=author&query=Middleton%2C+M">Michael Middleton</a>, <a href="/search/cs?searchtype=author&query=Mckendrick%2C+R">Ryan Mckendrick</a>, <a href="/search/cs?searchtype=author&query=Silva%2C+C">Claudio Silva</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2407.12260v1-abstract-short" style="display: inline;"> The concept of an intelligent augmented reality (AR) assistant has significant, wide-ranging applications, with potential uses in medicine, military, and mechanics domains. Such an assistant must be able to perceive the environment and actions, reason about the environment state in relation to a given task, and seamlessly interact with the task performer. These interactions typically involve an AR… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.12260v1-abstract-full').style.display = 'inline'; document.getElementById('2407.12260v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2407.12260v1-abstract-full" style="display: none;"> The concept of an intelligent augmented reality (AR) assistant has significant, wide-ranging applications, with potential uses in medicine, military, and mechanics domains. Such an assistant must be able to perceive the environment and actions, reason about the environment state in relation to a given task, and seamlessly interact with the task performer. These interactions typically involve an AR headset equipped with sensors which capture video, audio, and haptic feedback. Previous works have sought to facilitate the development of intelligent AR assistants by visualizing these sensor data streams in conjunction with the assistant's perception and reasoning model outputs. However, existing visual analytics systems do not focus on user modeling or include biometric data, and are only capable of visualizing a single task session for a single performer at a time. Moreover, they typically assume a task involves linear progression from one step to the next. We propose a visual analytics system that allows users to compare performance during multiple task sessions, focusing on non-linear tasks where different step sequences can lead to success. In particular, we design visualizations for understanding user behavior through functional near-infrared spectroscopy (fNIRS) data as a proxy for perception, attention, and memory as well as corresponding motion data (acceleration, angular velocity, and gaze). We distill these insights into embedding representations that allow users to easily select groups of sessions with similar behaviors. We provide two case studies that demonstrate how to use these visualizations to gain insights about task performance using data collected during helicopter copilot training tasks. Finally, we evaluate our approach by conducting an in-depth examination of a think-aloud experiment with five domain experts. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.12260v1-abstract-full').style.display = 'none'; document.getElementById('2407.12260v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">11 pages, 6 figures. This is the author's version of the article that has been accepted for publication in IEEE Transactions on Visualization and Computer Graphics (TVCG)</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2312.14036">arXiv:2312.14036</a> <span> [<a href="https://arxiv.org/pdf/2312.14036">pdf</a>, <a href="https://arxiv.org/format/2312.14036">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Sound">cs.SD</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Audio and Speech Processing">eess.AS</span> </div> </div> <p class="title is-5 mathjax"> Total variation in popular rap vocals from 2009-2023: extension of the analysis by Georgieva, Ripolles & McFee </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Walls%2C+K+L">Kelvin L Walls</a>, <a href="/search/cs?searchtype=author&query=Roman%2C+I+R">Iran R Roman</a>, <a href="/search/cs?searchtype=author&query=Steers%2C+B">Bea Steers</a>, <a href="/search/cs?searchtype=author&query=Georgieva%2C+E">Elena Georgieva</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2312.14036v1-abstract-short" style="display: inline;"> Pitch variability in rap vocals is overlooked in favor of the genre's uniquely dynamic rhythmic properties. We present an analysis of fundamental frequency (F0) variation in rap vocals over the past 14 years, focusing on song examples that represent the state of modern rap music. Our analysis aims at identifying meaningful trends over time, and is in turn a continuation of the 2023 analysis by Geo… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.14036v1-abstract-full').style.display = 'inline'; document.getElementById('2312.14036v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2312.14036v1-abstract-full" style="display: none;"> Pitch variability in rap vocals is overlooked in favor of the genre's uniquely dynamic rhythmic properties. We present an analysis of fundamental frequency (F0) variation in rap vocals over the past 14 years, focusing on song examples that represent the state of modern rap music. Our analysis aims at identifying meaningful trends over time, and is in turn a continuation of the 2023 analysis by Georgieva, Ripolles & McFee. They found rap to be an outlier with larger F0 variation compared to other genres, but with a declining trend since the genre's inception. However, they only analyzed data through 2010. Our analysis looks beyond 2010. We once again observe rap's large F0 variation, but with a decelerated decline in recent years. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.14036v1-abstract-full').style.display = 'none'; document.getElementById('2312.14036v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Ismir 2023 Hybrid Conference 2023 Nov 5 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2308.06246">arXiv:2308.06246</a> <span> [<a href="https://arxiv.org/pdf/2308.06246">pdf</a>, <a href="https://arxiv.org/format/2308.06246">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> ARGUS: Visualization of AI-Assisted Task Guidance in AR </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Castelo%2C+S">Sonia Castelo</a>, <a href="/search/cs?searchtype=author&query=Rulff%2C+J">Joao Rulff</a>, <a href="/search/cs?searchtype=author&query=McGowan%2C+E">Erin McGowan</a>, <a href="/search/cs?searchtype=author&query=Steers%2C+B">Bea Steers</a>, <a href="/search/cs?searchtype=author&query=Wu%2C+G">Guande Wu</a>, <a href="/search/cs?searchtype=author&query=Chen%2C+S">Shaoyu Chen</a>, <a href="/search/cs?searchtype=author&query=Roman%2C+I">Iran Roman</a>, <a href="/search/cs?searchtype=author&query=Lopez%2C+R">Roque Lopez</a>, <a href="/search/cs?searchtype=author&query=Brewer%2C+E">Ethan Brewer</a>, <a href="/search/cs?searchtype=author&query=Zhao%2C+C">Chen Zhao</a>, <a href="/search/cs?searchtype=author&query=Qian%2C+J">Jing Qian</a>, <a href="/search/cs?searchtype=author&query=Cho%2C+K">Kyunghyun Cho</a>, <a href="/search/cs?searchtype=author&query=He%2C+H">He He</a>, <a href="/search/cs?searchtype=author&query=Sun%2C+Q">Qi Sun</a>, <a href="/search/cs?searchtype=author&query=Vo%2C+H">Huy Vo</a>, <a href="/search/cs?searchtype=author&query=Bello%2C+J">Juan Bello</a>, <a href="/search/cs?searchtype=author&query=Krone%2C+M">Michael Krone</a>, <a href="/search/cs?searchtype=author&query=Silva%2C+C">Claudio Silva</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2308.06246v1-abstract-short" style="display: inline;"> The concept of augmented reality (AR) assistants has captured the human imagination for decades, becoming a staple of modern science fiction. To pursue this goal, it is necessary to develop artificial intelligence (AI)-based methods that simultaneously perceive the 3D environment, reason about physical tasks, and model the performer, all in real-time. Within this framework, a wide variety of senso… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.06246v1-abstract-full').style.display = 'inline'; document.getElementById('2308.06246v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2308.06246v1-abstract-full" style="display: none;"> The concept of augmented reality (AR) assistants has captured the human imagination for decades, becoming a staple of modern science fiction. To pursue this goal, it is necessary to develop artificial intelligence (AI)-based methods that simultaneously perceive the 3D environment, reason about physical tasks, and model the performer, all in real-time. Within this framework, a wide variety of sensors are needed to generate data across different modalities, such as audio, video, depth, speech, and time-of-flight. The required sensors are typically part of the AR headset, providing performer sensing and interaction through visual, audio, and haptic feedback. AI assistants not only record the performer as they perform activities, but also require machine learning (ML) models to understand and assist the performer as they interact with the physical world. Therefore, developing such assistants is a challenging task. We propose ARGUS, a visual analytics system to support the development of intelligent AR assistants. Our system was designed as part of a multi year-long collaboration between visualization researchers and ML and AR experts. This co-design process has led to advances in the visualization of ML in AR. Our system allows for online visualization of object, action, and step detection as well as offline analysis of previously recorded AR sessions. It visualizes not only the multimodal sensor data streams but also the output of the ML models. This allows developers to gain insights into the performer activities as well as the ML models, helping them troubleshoot, improve, and fine tune the components of the AR assistant. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.06246v1-abstract-full').style.display = 'none'; document.getElementById('2308.06246v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">11 pages, 8 figures. This is the author's version of the article of the article that has been accepted for publication in IEEE Transactions on Visualization and Computer Graphics</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.06220">arXiv:2203.06220</a> <span> [<a href="https://arxiv.org/pdf/2203.06220">pdf</a>, <a href="https://arxiv.org/format/2203.06220">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Sound">cs.SD</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Networking and Internet Architecture">cs.NI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Audio and Speech Processing">eess.AS</span> </div> </div> <p class="title is-5 mathjax"> Infrastructure-free, Deep Learned Urban Noise Monitoring at $\sim$100mW </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Yun%2C+J">Jihoon Yun</a>, <a href="/search/cs?searchtype=author&query=Srivastava%2C+S">Sangeeta Srivastava</a>, <a href="/search/cs?searchtype=author&query=Roy%2C+D">Dhrubojyoti Roy</a>, <a href="/search/cs?searchtype=author&query=Stohs%2C+N">Nathan Stohs</a>, <a href="/search/cs?searchtype=author&query=Mydlarz%2C+C">Charlie Mydlarz</a>, <a href="/search/cs?searchtype=author&query=Salman%2C+M">Mahin Salman</a>, <a href="/search/cs?searchtype=author&query=Steers%2C+B">Bea Steers</a>, <a href="/search/cs?searchtype=author&query=Bello%2C+J+P">Juan Pablo Bello</a>, <a href="/search/cs?searchtype=author&query=Arora%2C+A">Anish Arora</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.06220v1-abstract-short" style="display: inline;"> The Sounds of New York City (SONYC) wireless sensor network (WSN) has been fielded in Manhattan and Brooklyn over the past five years, as part of a larger human-in-the-loop cyber-physical control system for monitoring, analyzing, and mitigating urban noise pollution. We describe the evolution of the 2-tier SONYC WSN from an acoustic data collection fabric into a 3-tier in situ noise complaint moni… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.06220v1-abstract-full').style.display = 'inline'; document.getElementById('2203.06220v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.06220v1-abstract-full" style="display: none;"> The Sounds of New York City (SONYC) wireless sensor network (WSN) has been fielded in Manhattan and Brooklyn over the past five years, as part of a larger human-in-the-loop cyber-physical control system for monitoring, analyzing, and mitigating urban noise pollution. We describe the evolution of the 2-tier SONYC WSN from an acoustic data collection fabric into a 3-tier in situ noise complaint monitoring WSN, and its current evaluation. The added tier consists of long-range (LoRa), multi-hop networks of a new low-power acoustic mote, MKII ("Mach 2"), that we have designed and fabricated. MKII motes are notable in three ways: First, they advance machine learning capability at mote-scale in this application domain by introducing a real-time Convolutional Neural Network (CNN) based embedding model that is competitive with alternatives while also requiring 10$\times$ lesser training data and $\sim$2 orders of magnitude fewer runtime resources. Second, they are conveniently deployed relatively far from higher-tier base station nodes without assuming power or network infrastructure support at operationally relevant sites (such as construction zones), yielding a relatively low-cost solution. And third, their networking is frequency agile, unlike conventional LoRa networks: it tolerates in a distributed, self-stabilizing way the variable external interference and link fading in the cluttered 902-928MHz ISM band urban environment by dynamically choosing good frequencies using an efficient new method that combines passive and active measurements. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.06220v1-abstract-full').style.display = 'none'; document.getElementById('2203.06220v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Accepted in ICCPS 2022</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1903.03195">arXiv:1903.03195</a> <span> [<a href="https://arxiv.org/pdf/1903.03195">pdf</a>, <a href="https://arxiv.org/format/1903.03195">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Sound">cs.SD</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Audio and Speech Processing">eess.AS</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.3390/s19061415">10.3390/s19061415 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> The life of a New York City noise sensor network </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Mydlarz%2C+C">Charlie Mydlarz</a>, <a href="/search/cs?searchtype=author&query=Sharma%2C+M">Mohit Sharma</a>, <a href="/search/cs?searchtype=author&query=Lockerman%2C+Y">Yitzchak Lockerman</a>, <a href="/search/cs?searchtype=author&query=Steers%2C+B">Ben Steers</a>, <a href="/search/cs?searchtype=author&query=Silva%2C+C">Claudio Silva</a>, <a href="/search/cs?searchtype=author&query=Bello%2C+J+P">Juan Pablo Bello</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1903.03195v2-abstract-short" style="display: inline;"> Noise pollution is one of the topmost quality of life issues for urban residents in the United States. Continued exposure to high levels of noise has proven effects on health, including acute effects such as sleep disruption, and long-term effects such as hypertension, heart disease, and hearing loss. To investigate and ultimately aid in the mitigation of urban noise, a network of 55 sensor nodes… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1903.03195v2-abstract-full').style.display = 'inline'; document.getElementById('1903.03195v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1903.03195v2-abstract-full" style="display: none;"> Noise pollution is one of the topmost quality of life issues for urban residents in the United States. Continued exposure to high levels of noise has proven effects on health, including acute effects such as sleep disruption, and long-term effects such as hypertension, heart disease, and hearing loss. To investigate and ultimately aid in the mitigation of urban noise, a network of 55 sensor nodes has been deployed across New York City for over two years, collecting sound pressure level (SPL) and audio data. This network has cumulatively amassed over 75 years of calibrated, high-resolution SPL measurements and 35 years of audio data. In addition, high frequency telemetry data has been collected that provides an indication of a sensors' health. This telemetry data was analyzed over an 18 month period across 31 of the sensors. It has been used to develop a prototype model for pre-failure detection which has the ability to identify sensors in a prefail state 69.1% of the time. The entire network infrastructure is outlined, including the operation of the sensors, followed by an analysis of its data yield and the development of the fault detection approach and the future system integration plans for this. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1903.03195v2-abstract-full').style.display = 'none'; document.getElementById('1903.03195v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 March, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 7 March, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2019. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This article belongs to the Section Intelligent Sensors, 24 pages, 15 figures, 3 tables, 45 references</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Sensors 2019, 19, 1415 </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary">  <div class="column"> <div class="columns"> <div class="column"> <ul class="nav-spaced"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul class="nav-spaced"> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>contact arXiv</title><desc>Click here to contact arXiv</desc><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 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