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Kathryn Zyskowski, Meredith Ringel Morris, Jeffrey P. Bigham, Mary L. Gray, and Shaun Kane

We present the first formal study of crowdworkers who have disabilities via in-depth open-ended interviews of 17 people (disabled crowdworkers and job coaches for people with disabilities) and a survey of 631 adults with disabilities. Our findings establish that people with a variety of disabilities currently participate in the crowd labor marketplace, despite challenges such as crowdsourcing workflow designs that inadvertently prohibit participation by, and may negatively affect the worker reputations...

Publication details
Date: 1 March 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Jason D. Williams, Nobal B. Niraula, Pradeep Dasigi, Aparna Lakshmiratan, Carlos Garcia Jurado Suarez, Mouni Reddy, and Geoff Zweig

In personal assistant dialog systems, intent models are classifiers that identify the intent of a user utterance, such as to add a meeting to a calendar, or get the director of a stated movie. Rapidly adding intents is one of the main bottlenecks to scaling — adding functionality to — personal assistants. In this paper we show how interactive learning can be applied to the creation of statistical intent models. Interactive learning [10] combines model definition, labeling, model...

Publication details
Date: 11 January 2015
Type: Inproceeding
Robert A Cochran, Loris D’Antoni, Benjamin Livshits, David Molnar, and Margus Veanes

In this paper, we investigate an approach to program synthesis that is based on crowd-sourcing. With the help of crowd-sourcing, we aim to capture the “wisdom of the crowds” to find good if not perfect solutions to inherently tricky programming tasks, which elude even expert developers and lack an easy-to-formalize specification.

We propose an approach we call program boosting, which involves crowd-sourcing imperfect solutions to a difficult programming problem from developers and then...

Publication details
Date: 1 January 2015
Type: Proceedings
Publisher: ACM – Association for Computing Machinery
Xiaohu Liu and Ruhi Sarikaya

Spoken language understanding (SLU) systems use various features to detect the domain, intent and semantic slots of a query. In addition to n-grams, features generated from entity dictionaries are often used in model training. Clean or properly weighted dictionaries are critical to improve model’s coverage and accuracy for unseen entities during test time. However, clean dictionaries are hard to obtain for some applications since they are automatically generated and can potentially contain millions of...

Publication details
Date: 1 December 2014
Type: Proceedings
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Larry Heck and Hongzhao Huang

This paper presents an unsupervised neural knowledge graph embedding model and a coherence-based approach for semantic parsing of Twitter dialogs. The approach learns embeddings directly from knowledge graphs and scales to all of Wikipedia. Experiments show a 23.6% reduction in semanticparsing errors compared to the previously best reported results.

Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Kenton O'Hara, Gerardo Gonzalez, Abigail Sellen, Graeme Penney, Varnavas, Helena Mentis, Antonio Criminisi, Robert Corish, Mark Rouncefield, Neville Dastur, and Tom Carrell
Publication details
Date: 1 December 2014
Type: Article
Benjamin Livshits and George Kastrinis

Crowd-sourcing is increasingly being used for providing answers to online polls and surveys. However, existing systems, while taking care of the mechanics of attracting crowd workers, poll building, and payment, generally provide little by way of cost-management (e.g. working with a tight budget), time-management (e.g. obtaining results as quickly as possible), and controlling the margin of error (e.g. working on a sample population which is largely different from the general census statistics). The...

Publication details
Date: 14 November 2014
Type: Technical report
Number: MSR-TR-2014-145
Lucas Silva Figueiredo, Benjamin Livshits, David Molnar, and Margus Veanes
Publication details
Date: 14 November 2014
Type: Technical report
Number: MSR-TR-2014-146
Azadeh Forghani, Gina Venolia, and Kori Inkpen

Telephone calls and videoconferencing are ubiquitous parts of everyday life. As the content of the call may extend beyond just words, people share applications and media using techniques such as screen sharing and email attachments. Little is known about the prevalence of this behavior and the benefits it can provide. We conducted a survey and a lab study to examine media sharing during a video call and found that it can be useful as well as emotionally engaging. Participants indicated that they would...

Publication details
Date: 11 November 2014
Type: Inproceeding
Publisher: ACM
Neha Gupta, David Martin, Ben Hanrahan, and Jacki O'Neill

Previous studies on Amazon Mechanical Turk (AMT), the most well-known marketplace for microtasks, show that the largest population of workers on AMT is U.S. based, while the second largest is based in India. In this paper, we present insights from an ethnographic study conducted in India to introduce some of these workers or ‘Turkers’ – who they are, how they work and what turking means to them. We examine the work they do to maintain their reputations and their work-life balance. In doing this, we...

Publication details
Date: 9 November 2014
Type: Inproceeding
Publisher: ACM Conference on Supporting Groupwork
Katja Hofmann, Bhaskar Mitra, Filip Radlinski, and Milad Shokouhi

Query Auto Completion (QAC) suggests possible queries to web search users from the moment they start entering a query. This popular feature of web search engines is thought to reduce physical and cognitive effort when formulating a query.

Perhaps surprisingly, despite QAC being widely used, users’ interactions with it are poorly understood. This paper begins to address this gap. We present the results of an in-depth user study of user interactions with QAC in web search. While study participants...

Publication details
Date: 1 November 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Stuart Schechter and Cristian Bravo-Lillo

We update the ethical-response survey we published in July [9] to broaden its reach in two dimensions. In addition to surveying workers on Amazon's Mechanical Turk, we also reached out to juror candidates who had been summoned to serve at the King County Superior Court in Seattle, WA. In addition to five experimental scenarios we examined in prior surveys, we added seven new scenarios: two designed to serve as baselines of innocuousness and concern; two censorship-detection experiments that the Internet...

Publication details
Date: 1 November 2014
Type: Technical report
Number: MSR-TR-2014-140
Seungwon Kim, Sasa Junuzovic, and Kori Inkpen

Mobile videoconferencing is increasingly being used to bring remote friends or family along to an activity happening outside the home, such as shopping or visiting a tourist attraction. We explored how including contextual information of the event, in addition to audio and video of the person at the event, impacts the shared experience. We studied three kinds of information: a map showing the position of the person at the activity, a second live video showing what was in front of that person, and a...

Publication details
Date: 1 November 2014
Type: Inproceeding
Publisher: ACM
Danyel Fisher, Badrish Chandramouli, Robert DeLine, Jonathan Goldstein, Andrei Aron, Mike Barnett, John C. Platt, James F. Terwilliger, John Wernsing, danyelf badrishc, and rdeline jongold

Over the last two decades, data scientists performed increasingly sophisticated analyses on larger data sets, yet their tools and workflows remain low-level. A typical analysis involves different tools for different stages of the work, requiring file transfers and considerable care to keep everything organized. Temporal data adds additional complexity: users typically must write queries offline before porting them to production systems. To address these problems, this paper introduces Tempe, a web...

Publication details
Date: 1 November 2014
Type: Technical report
Publisher: Microsoft Research
Number: MSR-TR-2014-148
Stuart Schechter and Cristian Bravo-Lillo

We introduce a survey instrument for anticipating otherwise-unforeseen risks resulting from research experiments. We present experiments hypothetically, then ask: "If someone you cared about were a candidate participant for this experiment, would you want that person to be included as a participant?" (Q1) and "Do you believe the researchers should be allowed to proceed with this experiment?' (Q2). Having honed this approach over multiple studies, and multiple years, we have aborted proposed studies due...

Publication details
Date: 1 November 2014
Type: Technical report
Number: MSR-TR-2014-139
Wolf Kienzle and Ken Hinckley

We present LightRing, a wearable sensor in a ring form factor that senses the 2d location of a fingertip on any surface, independent of orientation or material. The device consists of an infrared proximity sensor for measuring finger flexion and a 1-axis gyroscope for measuring finger rotation. Notably, LightRing tracks subtle fingertip movements from the finger base without requiring instrumentation of other body parts or the environment. This keeps the normal hand function...

Publication details
Date: 1 October 2014
Type: Inproceeding
Publisher: ACM UIST
Michael Auli, Michel Galley, and Jianfeng Gao

Recent work by Cherry (2013) has shown that directly optimizing phrase-based reordering models towards BLEU can lead to significant gains. Their approach is limited to small training sets of a few thousand sentences and a similar number of sparse features. We show how the expected BLEU objective allows us to train a simple linear discriminative reordering model with millions of sparse features on hundreds of thousands of sentences resulting in significant improvements. A comparison to likelihood...

Publication details
Date: 1 October 2014
Type: Proceedings
Publisher: EMNLP
Sarah Mennicken, A. J. Bernheim Brush, Asta Roseway, and James Scott

People respond emotionally to other people, animals, or even objects like furniture. While current furniture is static in appearance, embedded electronics can enable furniture to change its appearance. A couch could show excitement during a party or anger when a pet scratches it. But would emotional furniture delight or annoy people? To explore the potential for emotional furniture, we built EmotoCouch. Through colored light, visual patterns, and haptic feedback, EmotoCouch expresses six emotional...

Publication details
Date: 15 September 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Sarah Mennicken, A. J. Bernheim Brush, Asta Roseway, and James Scott

Furniture is the building block of the spaces we inhabit. Its design and its functions shape how we use spaces, as individuals and as groups. While being an integral part of our lives, furniture is unaware of what happens around it. But what if furniture could change its appearance? What situations should it respond to? How might it communicate its state to those around it? Can we use emotional expression for such communication? To find and explore roles for interactive furniture in domestic spaces, we...

Publication details
Date: 13 September 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Dan Liebling and Sören Preibusch

Multiple vendors now provide relatively inexpensive desktop eye and gaze tracking devices. ith miniatureization and decreasing manufacturing costs, gaze trackers will follow the path of webcams, becoming ubiquitous and inviting many of the same privacy concerns. However, whereas the privacy loss from webcams may be obvious to the user, gaze tracking is more opaque and deserves special attention. In this paper, we review current research in gaze tracking and pupillometry and argue that gaze data should...

Publication details
Date: 13 September 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Daniel J. Liebling and Susan T. Dumais

Gaze tracking technology is increasingly common in desktop, laptop and mobile scenarios. Most previous research on eye gaze patterns during human-computer interaction has been confined to controlled laboratory studies. In this paper we present an in situ study of gaze and mouse coordination as participants went about their normal activities. We analyze the coordi-nation between gaze and mouse, showing that gaze often leads the mouse, but not as much as previously reported, and in ways that depend on the...

Publication details
Date: 13 September 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Alex Marin, Roman Holenstein, Ruhi Sarikaya, and Mari Ostendorf

This paper explores a novel method for learning phrase pattern features for text classification, employing a mapping of selected words into a knowledge graph and self-training over unlabeled data. Using Support Vector Machine classification, we obtain improvements over lexical and fully-supervised phrase pattern features in domain and intent detection for language understanding, particularly in conjunction with the use of unlabeled data. Our best results are obtained using unlabeled data filtered for...

Publication details
Date: 1 September 2014
Type: Proceedings
Publisher: ISCA - International Speech Communication Association
Xuxu Chen, Yu Zheng, Yubiao Chen, Qiwei Jin, Weiwei Sun, Eric Chang, and Wei-Ying Ma

Many developing countries are suffering from air pollution, especially the Particulate Matter with diameter of 2.5 micrometers or less (PM2.5). While quite a few air quality monitoring stations have been built by governments in a city’s public areas, the indoor PM2.5 has not yet been monitored and dealt with effectively. Though many office buildings have a HVAC (heating, ventilation, and air conditioning) system, PM2.5 is not considered as a factor when the system circulates fresh air from outdoors....

Publication details
Date: 1 September 2014
Type: Inproceeding
Publisher: ACM
Jean-Philippe Robichaud, Paul A. Crook, Puyang Xu, Omar Zia Khan, and Ruhi Sarikaya

We present a novel application of hypothesis ranking (HR) for the task of domain detection in a multi-domain, multiturn dialog system. Alternate, domain dependent, semantic frames from a spoken language understanding (SLU) analysis are ranked using a gradient boosted decision trees (GBDT) ranker to determine the most likely domain. The ranker, trained using Lambda Rank, makes use of a range of signals derived from the SLU and previous turn context to improve domain detection. On a multi-turn corpus we...

Publication details
Date: 1 September 2014
Type: Inproceeding
Publisher: ISCA - International Speech Communication Association
Michael Levit, Sarangarajan Parthasarathy, Shuangyu Chang, Andreas Stolcke, and Benoit Dumoulin

We present a modification of the traditional n-gram language modeling approach that departs from the word-level data representation and seeks to re-express the training text in terms of tokens that could be either words, common phrases or instances of one or several classes. Our iterative optimization algorithm considers alternative parses of the corpus in terms of these tokens, re-estimates token n-gram probabilities and also updates within-class distributions. In this paper, we focus on the cold start...

Publication details
Date: 1 September 2014
Type: Inproceeding
Publisher: ISCA - International Speech Communication Association
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