Jennifer Lai
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Publications by Jennifer Lai (bibliography)
» 2009 «
Wilcox, Lauren, Lu, Jie, Lai, Jennifer, Feiner, Steven K. and Jordan, Desmond (2009): ActiveNotes: computer-assisted creation of patient progress notes. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 3323-3328. Available online
“We present activeNotes, a prototype application that supports the creation of Critical Care Notes by physicians in a hospital intensive care unit. activeNotes integrates automated, context-sensitive patient data retrieval and user control of automated data updates and alerts into the note-creation process. In a user study at New York Presbyterian Hospital, we gathered qualitative feedback on the prototype from 15 physicians. The physicians found activeNotes to be valuable and said they would use it to create both formal notes for medical records and informal notes. One surprising finding is that while physicians have rejected template-based clinical documentation systems in the past, they expressed a desire to use activeNotes to create personalized, physician-specific note templates to be reused with a given patient, or for a given condition.”
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» 2008 «
Hsieh, Gary, Lai, Jennifer, Hudson, Scott E. and Kraut, Robert E. (2008): Using tags to assist near-synchronous communication. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 223-226. Available online
“In this work, we introduce the use of tags to support the near synchronous use of instant messaging. As a proof-of-concept, we developed a plug-in in Lotus Sametime, an enterprise IM client. Our plug-in supports tasks that do not need immediate attention and tasks that have deadlines. A trial deployment and survey shows that users can see the potential usefulness of such a tagging system in their IM communication. Furthermore, users rated our design intuitive and easy to use. Longer study is needed to explore communication norms that results from its use.”
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Singley, Kevin, Lai, Jennifer, Kuang, Lei and Tang, Jung-Mu (2008): Bluereach: harnessing synchronous chat to support expertise sharing in a large organization. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 2001-2008. Available online
“We present a case study of BlueReach, an expertise sharing application that uses synchronous chat to connect question askers with subject-matter experts. We discuss how the solution evolved over time, and the generally high level of acceptance from users and volunteer experts. We include survey findings and usage data, which indicate that in spite of initial concerns that the experts would be overwhelmed by questions, usage has been fairly low and relatively flat. We examine this phenomenon and conclude with a discussion of lessons learned.”
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» 2007 «
Brodie, Mark, Lai, Jennifer, Lenchner, Jonathan, Luken, William, Ranganathan, Kavitha, Tang, Jung-Mu and Vukovic, Maja (2007): Support Services: Persuading Employees and Customers to Do what Is in the Community's Best Interest. In: Kort, Yvonne de, IJsselsteijn, Wijnand, Midden, Cees J. H., Eggen, Berry and Fogg, B. J. (eds.) PERSUASIVE 2007 - Persuasive Technology, Second International Conference on Persuasive Technology April 26-27, 2007, Palo Alto, CA, USA. pp. 121-124. Available online
Huffaker, David and Lai, Jennifer (2007): Motivating Online Expertise-Sharing for Informal Learning: The Influence of Age and Tenure in Knowledge Organizations. In: Spector, J. Michael, Sampson, Demetrios G., Okamoto, Toshio, Cerri, Stefano A., Ueno, Maomi and Kashihara, Akihiro (eds.) ICALT 2007 - Proceedings of the 7th IEEE International Conference on Advanced Learning Technologies July 18-20, 2007, Niigata, Japan. pp. 595-599. Available online
Grueneberg, Keith, Katriel, Amy, Lai, Jennifer and Feng, Jing (2007): Reading Companion: A Interactive Web-Based Tutor for Increasing Literacy Skills. In: Baranauskas, Maria Cecília Calani, Palanque, Philippe A., Abascal, Julio and Barbosa, Simone Diniz Junqueira (eds.) DEGAS 2007 - Proceedings of the 1st International Workshop on Design and Evaluation of e-Government Applications and Services September 11th, 2007, Rio de Janeiro, Brazil. pp. 345-348. Available online
» 2005 «
Patil, Sameer and Lai, Jennifer (2005): Who gets to know what when: configuring privacy permissions in an awareness application. In: Proceedings of ACM CHI 2005 Conference on Human Factors in Computing Systems 2005. pp. 101-110. Available online
“We report on a study (N=36) of user preferences for balancing awareness with privacy. Participants defined permissions for sharing of location, availability, calendar information and instant messaging (IM) activity within an application called mySpace. MySpace is an interactive visualization of the physical workplace that provides dynamic information about people, places and equipment. We found a significant preference for defining privacy permissions at the group level. While "family" received high levels of awareness sharing, interestingly, "team" was granted comparable levels during business hours at work. Surprisingly, presenting participants with a detailed list of all pieces of personal context to which the system had access, did not result in more conservative privacy settings. Although location was the most sensitive aspect of awareness, participants were comfortable disclosing room-level location information to their team members at work. Our findings suggest utilizing grouping mechanisms to balance privacy control with configuration burden, and argue for increased system transparency to build trust.”
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Lee, Kwan Min and Lai, Jennifer (2005): Speech Versus Touch: A Comparative Study of the Use of Speech and DTMF Keypad for Navigation. In International Journal of Human-Computer Interaction, 19 (3) pp. 343-360
“This article reports on an experiment that critically tests user preference for an input modality (speech vs. Dual Tone Multiple Frequency[DTMF])in a phone-based message retrieval system. Unlike previous studies that compared these two modalities, the speech system used in this study was a fully functioning natural language system, and participants in this study were working professionals, rather than college students. Results indicate that (a) DTMF was more effective and efficient for linear tasks, whereas speech was better for nonlinear tasks; (b) speech was preferred to DTMF by a majority of users; (c) speech was judged as being more satisfying, more entertaining, and easier to use than DTMF; and (d) user preference for a particular modality was better predicted by user performance in nonlinear tasks rather than linear ones. Possible reasons for users' continuing preference for the speech modality even after experiencing fairly high recognition errors are discussed. Finally, the importance of examining speech user interfaces from other perspectives, in addition to efficiency maximization, is emphasized. The results of this study have theoretical, as well as practical, implications for the design of speech user interfaces and interactive voice response applications.”
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» 2004 «
Fogarty, James, Hudson, Scott E. and Lai, Jennifer (2004): Examining the robustness of sensor-based statistical models of human interruptibility. In: Dykstra-Erickson, Elizabeth and Tscheligi, Manfred (eds.) Proceedings of ACM CHI 2004 Conference on Human Factors in Computing Systems April 24-29, 2004, Vienna, Austria. pp. 207-214. Available online
“Current systems often create socially awkward interruptions or unduly demand attention because they have no way of knowing if a person is busy and should not be interrupted. Previous work has examined the feasibility of using sensors and statistical models to estimate human interruptibility in an office environment, but left open some questions about the robustness of such an approach. This paper examines several dimensions of robustness in sensor-based statistical models of human interruptibility. We show that real sensors can be constructed with sufficient accuracy to drive the predictive models. We also create statistical models for a much broader group of people than was studied in prior work. Finally, we examine the effects of training data quantity on the accuracy of these models and consider tradeoffs associated with different combinations of sensors. As a whole, our analyses demonstrate that sensor-based statistical models of human interruptibility can provide robust estimates for a variety of office workers in a range of circumstances, and can do so with accuracy as good as or better than people. Integrating these models into systems could support a variety of advances in human computer interaction and computer-mediated communication.”
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Fogarty, James, Lai, Jennifer and Christensen, Jim (2004): Presence versus availability: the design and evaluation of a context-aware communication client. In International Journal of Human-Computer Studies, 61 (3) pp. 299-317
“Although electronic communication plays an important role in the modern workplace, the interruptions created by poorly-timed attempts to communicate are disruptive. Prior work suggests that sharing an indication that a person is currently busy might help to prevent such interruptions, because people could wait for a person to become available before attempting to initiate communication. We present a context-aware communication client that uses the built-in microphones of laptop computers to sense nearby speech. Combining this speech detection sensor data with location, computer, and calendar information, our system models availability for communication, a concept that is distinct from the notion of presence found in widely-used systems. In a 4 week study of the system with 26 people, we examined the use of this additional context. To our knowledge, this is the first-field study to quantitatively examine how people use automatically sensed context and availability information to make decisions about when and how to communicate with colleagues. Participants appear to have used the provided context to as an indication of presence, rather than considering availability. Our results raise the interesting question of whether sharing an indication that a person is currently unavailable will actually reduce inappropriate interruptions.”
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» 2003 «
Lai, Jennifer, Yoshihama, Sachiko, Bridgman, Thomas, Podlaseck, Mark, Chou, Paul and Wong, Danny (2003): MyTeam: Availability Awareness Through the Use of Sensor Data. In: Proceedings of IFIP INTERACT03: Human-Computer Interaction 2003, Zurich, Switzerland. p. 503.
Gong, Li and Lai, Jennifer (2003): To mix or not to mix synthetic speech and human speech? Contrasting impact on judge-rated task performance versus self-rated performance and attitudinal responses. In International Journal of Speech Technology, 6 pp. 123-131
» 2002 «
Lai, Jennifer, Levas, Anthony, Chou, Paul, Pinhanez, Claudio S. and Viveros, Marisa (2002): BlueSpace: personalizing workspace through awareness and adaptability. In International Journal of Human-Computer Studies, 57 (5) pp. 415-428
“This paper reports on research in workplace issues encountered by knowledge
workers in cubicle environments, and on BlueSpace, a prototype workspace with
the goal of addressing workers' critical needs for privacy, concentration and
personalization. To inform the design process, more than 50 on-site interviews
with knowledge workers were conducted at six companies ranging from dot.com
startups to Fortune 100 corporations. Several common requirements emerged
including the need for a sense of control of one's workspace, the ability to
create privacy on-demand to improve concentration and minimize unwanted
interruptions, as well as in-place support for dyadic interactions. Many other
common workplace complaints (e.g. too hot, too cold, too noisy) were found to
be derivative of the major requirements for individual control and privacy.”
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» 2001 «
Gong, Li and Lai, Jennifer (2001): Shall we Mix Synthetic Speech and Human Speech?: Impact on Users' Performance, Perception, and Attitude. In: Beaudouin-Lafon, Michel and Jacob, Robert J. K. (eds.) Proceedings of the ACM CHI 2001 Human Factors in Computing Systems Conference March 31 - April 5, 2001, Seattle, Washington, USA. pp. 158-165. Available online
“Because it is impractical to record human voice for ever-changing dynamic content such as email messages and news, many commercial speech applications use human speech for fixed prompts and synthetic speech (TTS) for the dynamic content. However, this mixing approach may not be optimal from a consistency perspective. A 2-condition between-group experiment (N = 24) was conducted to compare two versions of a virtual-assistant interface (mixing human voice and TTS vs. TTS-only). Users interacted with the virtual assistant to manage some email and calendar tasks. Their task performance, self-perception of task performance, and attitudinal responses were measured. Users interacting with the TTS-only interface performed the task significantly better, while users interacting with the mixed-voices interface thought they did better and had more positive attitudinal responses. Explanations and design implications are suggested.”
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Lai, Jennifer, Cheng, Karen, Green, Paul and Tsimhoni, Omer (2001): On the Road and on the Web?: Comprehension of Synthetic and Human Speech While Driving. In: Beaudouin-Lafon, Michel and Jacob, Robert J. K. (eds.) Proceedings of the ACM CHI 2001 Human Factors in Computing Systems Conference March 31 - April 5, 2001, Seattle, Washington, USA. pp. 206-212. Available online
“In this study 24 participants drove a simulator while listening to three types of messages in both synthesized speech and recorded human speech. The messages consisted of short navigation messages, medium length (approximately 100 words) email messages, and longer news stories (approximately 200 words). After each message the participant was presented with a series of multiple choice questions to measure comprehension of the message. Driving performance was recorded. Findings show that for the low driving workload conditions in the study, (cruise control, predictable two-lane road with no intersections, invariant lead car) driving performance was not affected by listening to messages. This was true for both the synthesized speech and natural speech. Comprehension of messages in synthetic speech was significantly lower than for recorded human speech for all message types.”
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» 2000 «
Lai, Jennifer, Wood, David and Considine, Michael (2000): The Effect of Task Conditions on the Comprehensibility of Synthetic Speech. In: Turner, Thea, Szwillus, Gerd, Czerwinski, Mary, Peterno, Fabio and Pemberton, Steven (eds.) Proceedings of the ACM CHI 2000 Human Factors in Computing Systems Conference April 1-6, 2000, The Hague, The Netherlands. pp. 321-328. Available online
“A study was conducted with 78 subjects to evaluate the comprehensibility of synthetic speech for various tasks ranging from short, simple e-mail messages to longer news articles on mostly obscure topics. Comprehension accuracy for each subject was measured for synthetic speech and for recorded human speech. Half the subjects were allowed to take notes while listening, the other half were not. Findings show that there was no significant difference in comprehension of synthetic speech among the five different text-to-speech engines used. Those subjects that did not take notes performed significantly worse for all synthetic voice tasks when compared to recorded speech tasks. Performance for synthetic speech in the non note-taking condition degraded as the task got longer and more complex. When taking notes, subjects also did significantly worse within the synthetic voice condition averaged across all six tasks. However, average performance scores for the last three tasks in this condition show comparable results for human and synthetic speech, reflective of a training effect.”
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» 1997 «
Lai, Jennifer and Vergo, John (1997): MedSpeak: Report Creation with Continuous Speech Recognition. In: Pemberton, Steven (ed.) Proceedings of the ACM CHI 97 Human Factors in Computing Systems Conference March 22-27, 1997, Atlanta, Georgia. pp. 431-438. Available online
“MedSpeak/Radiology is a product that allows radiologists to create, edit and manage reports using real-time, continuous speech recognition. Speech is used both to navigate through the application, and to dictate reports. The system is multi-modal, accepting input by either voice, mouse or keyboard. This paper reports on how we addressed the critical user need of high throughput in our interface design, and ways of supporting both error prevention and error correction with continuous speech. User studies suggest that for this task”
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Mar 18th, 2010
Changes to this page (author)
12 Feb 2010: Enabled abstracts to be shown on Jennifer Lai's author page.25 Jul 2009: Author was edited 17 Jun 2009: Author was edited
17 Jun 2009: Author was edited
09 May 2009: Author was edited
03 Feb 2009: Author was added to the bibliography (approved by an editor)
12 May 2008: Author was edited
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28 Apr 2003: Added the author to the bibliography
